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Add GPT-6 Astra 1× + ICL native evaluation logs (#2)

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- Add GPT-6 Astra 1× + ICL native evaluation logs (7562e4f8d4e3cec1f3681922c68a8b72c735d205)
- Record historical missing-log and rerun audit hashes (cf97cb8a32fe699dc29c9aa6a822e58aae1500dc)


Co-authored-by: Quanzhou Li <licandow@users.noreply.huggingface.co>

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1
+ # GPT-6 Astra — 1× + ICL
2
+
3
+ This entry reports the **Full / unseen** Bench2Dex channel for GPT-6 Astra with
4
+ frozen per-task in-context preparation. The policy uses RGB camera observations,
5
+ proprioception, and a task description; the model runs with max reasoning effort.
6
+ Task-related preparation is frozen before test episodes, and each test episode
7
+ uses an isolated model session. The evaluation uses the upstream stable-success
8
+ and latched-stage metrics at 60 Hz physics and 20 Hz control.
9
+
10
+ [Technical report](https://www.sensenova.ai/has-gpt-6-astra-achieved-embodied-intelligence)
11
+ · [SenseNova-RoboRSI project](https://github.com/OpenSenseNova/SenseNova-RoboRSI)
12
+
13
+ ## Result and coverage
14
+
15
+ - **Stable success rate:** 68/260 = **26.15%**.
16
+ - **Latched stage completion rate:** **48.77%**, averaged equally over 26 tasks.
17
+ - **Coverage:** 26 tasks × 10 Full-channel episodes = 260 episodes. The reference
18
+ protocol uses 50 episodes per task and channel.
19
+ - **Efficiency:** not reported because the retained aggregate evidence does not
20
+ establish the successful-step/expert-reference inputs for every selected episode.
21
+ - **Other channels:** None, Equi., and Inv. were not evaluated in this cohort;
22
+ the four-channel mean is therefore not reported.
23
+
24
+ ## Evaluation protocol
25
+
26
+ The selected indices 5–14 form a 260-episode Full-channel cohort. Seventeen damaged outcomes use same-index certified replacements. Task 61 episode 8 was additionally rerun at its original index and seed because its original native evaluator log was lost. The rerun's first valid outcome was selected regardless of success; the original recorded success and 100% LSCR remain historical evidence, not the selected score. The cohort is an amended reporting selection.
27
+
28
+ The official 1× task budget is `ceil(1.5 × expert_time_step / 3)` policy steps,
29
+ with three physics steps per action row. The JSON gives each task's actual 1×
30
+ budget, the 1× allowance, seeds, and episode indices.
31
+ The two entries must be interpreted as separate evaluation settings.
32
+
33
+ The 1× source cohort includes provenance-selected damage replacements; a full
34
+ archive certification was not completed. Historical Task 22/26 extensions and
35
+ the partly unresolved Task 51 preparation provenance are disclosed limitations.
36
+
37
+ The linked Hugging Face dataset entry includes the selected native Bench2Dex
38
+ evaluator rows, sanitized single-episode source logs and summaries under
39
+ `source_runs/`, and a SHA-256 provenance manifest. The per-task summaries are
40
+ recomputed with the upstream Bench2Dex summary writer from the selected rows.
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+ }
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+ },
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+ "expertReference": "Bench2Dex scene expert_time_step at benchmarkCommit",
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+ "protocolChanges": [
1685
+ "Full/unseen only; 10 episodes per task rather than the 50-episode reference.",
1686
+ "17 same-index damage-recovery replacements were selected by provenance, not outcome.",
1687
+ "Task 61 episode 8 was rerun at its original index/seed because its original native evaluator log was lost; the new valid outcome replaces that reporting slot."
1688
+ ]
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+ },
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+ "coverage": {
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+ "evaluatedTaskCount": 26,
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+ "evaluatedEpisodeCount": 260,
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+ "Full": 26,
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+ },
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+ "expectedFullEpisodeCount": 1300,
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+ "expectedFourChannelEpisodeCount": 5200,
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+ "03": [
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1705
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+ ],
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+ ],
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+ ],
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+ ],
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+ "Inv."
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+ ]
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+ }
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+ },
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+ "aggregation": {
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+ "units": {
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+ "sr": "percent",
1838
+ "lscr": "percent",
1839
+ "efficiency": "ratio",
1840
+ "steps": "physics_steps"
1841
+ },
1842
+ "sr": "100 * successes / episodes per task/channel; equal channel mean per task; equal task mean over all 26 settings.",
1843
+ "lscr": "100 * mean episode latched_stage_completion_rate, including failures; equal channel mean per task; equal task mean over all 26 settings.",
1844
+ "efficiency": "expert_time_step / mean successful steps_to_stable_success. Pool successful episodes across all four channels before calculating task mean efficiency. Overall values average task efficiencies over tasks with success; report valid-task counts.",
1845
+ "missing": "null means unreported (NR). Efficiency without successes is null with no-success status. Valid-task counts are null when unreported, and 0 for an evaluated scope without successes.",
1846
+ "scope": "Overall channel aggregates require all 26 settings. Four-channel means require all four channels. Never substitute Full-only scores for means or include duplicate reruns."
1847
+ },
1848
+ "logs": {
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+ "repository": "Bench2Dex/Leaderboard",
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+ "policyPath": "gpt6_astra_1x_icl",
1851
+ "revision": null,
1852
+ "status": "not-archived"
1853
+ }
1854
+ }
1855
+ }
gpt6_astra_1x_icl/per_task_eval/03_wine_glass_plate_balance/Full/per_episode.jsonl ADDED
The diff for this file is too large to render. See raw diff
 
gpt6_astra_1x_icl/per_task_eval/03_wine_glass_plate_balance/Full/summary.json ADDED
@@ -0,0 +1,212 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "metric_schema_version": "core-v1.8-policy-step-query-split",
3
+ "metadata": {
4
+ "policy_name": "gpt-6-astra",
5
+ "base_seed": 200300000,
6
+ "seed_policy": "episode_seed = base_seed + episode_index - 1",
7
+ "randomization_recorded": true,
8
+ "n_episodes": 10,
9
+ "successes": 0,
10
+ "error_count": 0,
11
+ "evaluation_protocol": "reach_and_stop",
12
+ "early_stop": true,
13
+ "success_definition": "terminal.raw_condition holds for dwell_time_s",
14
+ "measurement_window": "episode_start_to_stable_success_or_failure_budget",
15
+ "max_episode_steps": 3246,
16
+ "dwell_time_s": 0.5,
17
+ "field_semantics": {
18
+ "success_rate": "primary protocol success rate: stable_success for reach_and_stop; terminal at_end_success_budget for fixed_horizon",
19
+ "avg_time_to_success_s": "main efficiency metric: mean time_to_stable_success_s over reached-success episodes",
20
+ "task_efficiency": "benchmark-specific expert-normalized speed ratio: expert_time_s / time_to_stable_success_s over reached-success episodes",
21
+ "avg_steps_to_success": "diagnostic mean steps_to_stable_success over reached-success episodes, or None if no episode succeeds",
22
+ "avg_policy_steps_to_success": "diagnostic mean policy-rate control/action steps through stable success over reached-success episodes",
23
+ "avg_policy_queries_to_success": "diagnostic mean actual model inference queries through stable success over reached-success episodes; None when the first-success query count was not observed",
24
+ "safe_success_rate": "episode success rate with no task-level hard safety violation (drop or tracked-object high speed; joint limits are diagnostic by default)",
25
+ "hard_violation_rate": "episode rate with any task-level hard safety violation (drop or tracked-object high speed; joint limits are diagnostic by default)",
26
+ "drop_rate": "episode rate with drop_off_table or drop_to_table_after_lift violation",
27
+ "high_speed_violation_rate": "episode rate with any tracked object exceeding the configured speed threshold",
28
+ "excessive_impact_rate": "deprecated contact-force impact metric; no longer populated by core safety",
29
+ "robot_constraint_violation_rate": "diagnostic episode rate with any asset hard-joint-limit observation; excluded from safe_success_rate unless include_in_core_safety is explicitly enabled",
30
+ "finger_joint_limit_saturation_rate": "episode rate with dexterous finger joints saturated beyond finger joint-limit thresholds; diagnostic by default and not included in safe_success_rate",
31
+ "joint_limit_active_step_rate": "diagnostic mean fraction of steps with any joint exceeding the soft diagnostic margin",
32
+ "finger_joint_limit_saturation_step_rate": "diagnostic mean fraction of steps with finger joint-limit saturation",
33
+ "max_joint_limit_excess_rad": "diagnostic maximum operating/soft-limit excess observed in radians; hard-limit source and role validation are in robot_constraint_diagnostics",
34
+ "safety_violation_rate_time": "compatibility diagnostic; with fixed physics_dt this is equivalent to safety_violation_step_rate and is omitted from grouped summary output",
35
+ "safety_violation_step_rate": "core safety metric: fraction of executed steps with task-level safety violations; joint-limit observations are excluded by default",
36
+ "safety_violation_rate_event": "deprecated compatibility alias of safety_violation_events_per_step; omitted from grouped summary output",
37
+ "safety_violation_events_per_step": "diagnostic event density; may exceed 1 when multiple violations happen in one step",
38
+ "episode_violation_rate": "compatibility alias of hard_violation_rate; omitted from grouped core output",
39
+ "latched_stage_completion_rate": "main progress metric; ever-reached stage completion rate at episode end",
40
+ "current_stage_completion_rate": "diagnostic terminal-state stage completion rate at episode end",
41
+ "current_normalized_progress_score": "chain-depth diagnostic; normalized progress score at episode end",
42
+ "current_chain_depth_progress_score": "alias of current_normalized_progress_score for ordered dependency-depth diagnostics",
43
+ "latched_chain_depth_progress_score": "alias of latched_normalized_progress_score for ever-reached dependency-depth diagnostics",
44
+ "robustness": "success rates grouped by benchmark protocol category: cov, inv, and inv+cov"
45
+ }
46
+ },
47
+ "core_metrics": {
48
+ "completion": {
49
+ "success_rate": 0.0,
50
+ "success_rate_ci": {
51
+ "mean": 0.0,
52
+ "ci_low": 0.0,
53
+ "ci_high": 0.0
54
+ }
55
+ },
56
+ "progress": {
57
+ "latched_stage_completion_rate": 0.39999999999999997
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+ },
59
+ "efficiency": {
60
+ "avg_time_to_success_s": null
61
+ },
62
+ "safety": {
63
+ "safe_success_rate": 0.0,
64
+ "hard_violation_rate": 0.9,
65
+ "drop_rate": 0.9,
66
+ "high_speed_violation_rate": 0.1,
67
+ "safety_violation_step_rate": 0.04460874922982132
68
+ },
69
+ "robustness": {}
70
+ },
71
+ "diagnostic_metrics": {
72
+ "completion": {
73
+ "ever_instant_success_rate": 0.0,
74
+ "at_end_success_rate": 0.0,
75
+ "task_family_success_rate": {
76
+ "table_setting": 0.0
77
+ }
78
+ },
79
+ "progress": {
80
+ "current_stage_completion_rate": 0.16666666666666666,
81
+ "current_chain_depth_progress_score": 0.16666666666666666,
82
+ "latched_chain_depth_progress_score": 0.39999999999999997,
83
+ "avg_current_chain_depth": 0.5,
84
+ "avg_latched_chain_depth": 1.2
85
+ },
86
+ "efficiency": {
87
+ "task_efficiency": null,
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+ "expert_time_s": 36.06666666666666,
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+ "expert_time_step": 2164,
90
+ "avg_steps_to_success": null,
91
+ "avg_policy_steps_to_success": null,
92
+ "avg_policy_queries_to_success": null
93
+ },
94
+ "safety": {
95
+ "safety_violation_events_per_step": 0.0004313000616142945,
96
+ "violation_counts": {
97
+ "drop_obj_194_wineglass_1": 1,
98
+ "drop_to_table_obj_194_wineglass_1": 9,
99
+ "drop_to_table_obj_194_wineglass_2": 1,
100
+ "drop_to_table_obj_194_wineglass_3": 2,
101
+ "high_speed_obj_194_wineglass_1": 1
102
+ },
103
+ "robot_constraint_violation_rate": 0.7,
104
+ "finger_joint_limit_saturation_rate": 0.0,
105
+ "joint_limit_active_step_rate": 0.0012630930375847197,
106
+ "finger_joint_limit_saturation_step_rate": 0.0,
107
+ "max_joint_limit_excess_rad": 0.06860432028770447,
108
+ "robot_constraint_diagnostics": {
109
+ "joint_limit_soft_counts": {
110
+ "middle_q2": 29,
111
+ "multi_pinky_q1": 3,
112
+ "multi_ring_q1": 1,
113
+ "multi_ring_q2": 8
114
+ },
115
+ "joint_limit_hard_counts": {
116
+ "middle_q2": 1,
117
+ "multi_pinky_q1": 2,
118
+ "multi_ring_q1": 3,
119
+ "multi_ring_q2": 2,
120
+ "ring_q1": 1
121
+ },
122
+ "joint_limit_hard_episode_events": 9,
123
+ "finger_joint_limit_saturation_counts": {},
124
+ "joint_limit_max_excess_by_joint": {
125
+ "index_q1": 0.0030562784522771835,
126
+ "index_q2": 2.8614797198400765e-09,
127
+ "middle_q1": 0.0012579697649925947,
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+ "middle_q2": 0.05049429088830948,
129
+ "multi_index_q1": 0.00476967403665185,
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+ "multi_index_q2": 2.294862300189493e-09,
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+ "multi_middle_q1": 0.002055603312328458,
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+ "multi_middle_q2": 0.001359704416245222,
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+ "multi_pinky_q1": 0.026384813711047173,
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+ "multi_pinky_q2": 0.0026463610120117664,
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+ "multi_ring_q1": 0.0110697066411376,
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+ "multi_ring_q2": 0.06860432028770447,
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+ "multi_thumb_q1": 0.0005444049602374434,
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+ "multi_thumb_q2": 0.00013726763427257538,
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+ "pinky_q1": 0.001833398942835629,
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+ "thumb_q2": 0.0006376263336278498
145
+ },
146
+ "coverage": {
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+ "hard_limit_source": {
148
+ "available": 10,
149
+ "unavailable": 0,
150
+ "unknown": 0
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+ },
152
+ "joint_role_manifest": {
153
+ "available": 10,
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+ "unavailable": 0,
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+ "unknown": 0
156
+ }
157
+ },
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+ "hard_limit_sources": {
159
+ "runtime.joint_pos_limits": 10
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+ },
161
+ "soft_limit_sources": {
162
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gpt6_astra_1x_icl/per_task_eval/06_fruit_bowl_loading/Full/per_episode.jsonl ADDED
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gpt6_astra_1x_icl/per_task_eval/06_fruit_bowl_loading/Full/summary.json ADDED
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1
+ {
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+ "metadata": {
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+ "policy_name": "gpt-6-astra",
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+ "base_seed": 200600000,
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+ "seed_policy": "episode_seed = base_seed + episode_index - 1",
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+ "max_episode_steps": 1920,
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+ "dwell_time_s": 0.5,
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+ "field_semantics": {
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+ "success_rate": "primary protocol success rate: stable_success for reach_and_stop; terminal at_end_success_budget for fixed_horizon",
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+ "avg_time_to_success_s": "main efficiency metric: mean time_to_stable_success_s over reached-success episodes",
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+ "task_efficiency": "benchmark-specific expert-normalized speed ratio: expert_time_s / time_to_stable_success_s over reached-success episodes",
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+ "avg_steps_to_success": "diagnostic mean steps_to_stable_success over reached-success episodes, or None if no episode succeeds",
22
+ "avg_policy_steps_to_success": "diagnostic mean policy-rate control/action steps through stable success over reached-success episodes",
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+ "avg_policy_queries_to_success": "diagnostic mean actual model inference queries through stable success over reached-success episodes; None when the first-success query count was not observed",
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+ "safe_success_rate": "episode success rate with no task-level hard safety violation (drop or tracked-object high speed; joint limits are diagnostic by default)",
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+ "hard_violation_rate": "episode rate with any task-level hard safety violation (drop or tracked-object high speed; joint limits are diagnostic by default)",
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+ "drop_rate": "episode rate with drop_off_table or drop_to_table_after_lift violation",
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+ "high_speed_violation_rate": "episode rate with any tracked object exceeding the configured speed threshold",
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+ "excessive_impact_rate": "deprecated contact-force impact metric; no longer populated by core safety",
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+ "finger_joint_limit_saturation_rate": "episode rate with dexterous finger joints saturated beyond finger joint-limit thresholds; diagnostic by default and not included in safe_success_rate",
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+ "joint_limit_active_step_rate": "diagnostic mean fraction of steps with any joint exceeding the soft diagnostic margin",
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+ "safety_violation_rate_time": "compatibility diagnostic; with fixed physics_dt this is equivalent to safety_violation_step_rate and is omitted from grouped summary output",
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+ "safety_violation_step_rate": "core safety metric: fraction of executed steps with task-level safety violations; joint-limit observations are excluded by default",
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+ "safety_violation_rate_event": "deprecated compatibility alias of safety_violation_events_per_step; omitted from grouped summary output",
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+ "safety_violation_events_per_step": "diagnostic event density; may exceed 1 when multiple violations happen in one step",
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+ "episode_violation_rate": "compatibility alias of hard_violation_rate; omitted from grouped core output",
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+ "latched_stage_completion_rate": "main progress metric; ever-reached stage completion rate at episode end",
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+ "current_stage_completion_rate": "diagnostic terminal-state stage completion rate at episode end",
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+ "current_normalized_progress_score": "chain-depth diagnostic; normalized progress score at episode end",
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+ "current_chain_depth_progress_score": "alias of current_normalized_progress_score for ordered dependency-depth diagnostics",
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+ "latched_chain_depth_progress_score": "alias of latched_normalized_progress_score for ever-reached dependency-depth diagnostics",
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+ "robustness": "success rates grouped by benchmark protocol category: cov, inv, and inv+cov"
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+ }
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+ "unknown_runtime_joint_names": [],
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+ "baseline_checks": {
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+ "per_object_best_kinematic_grasp_stability": {
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+ }
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gpt6_astra_1x_icl/per_task_eval/07_citrus_plate_loading/Full/per_episode.jsonl ADDED
The diff for this file is too large to render. See raw diff
 
gpt6_astra_1x_icl/per_task_eval/07_citrus_plate_loading/Full/summary.json ADDED
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1
+ {
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+ "metadata": {
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+ "policy_name": "gpt-6-astra",
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+ "seed_policy": "episode_seed = base_seed + episode_index - 1",
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+ "success_rate": "primary protocol success rate: stable_success for reach_and_stop; terminal at_end_success_budget for fixed_horizon",
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+ "avg_time_to_success_s": "main efficiency metric: mean time_to_stable_success_s over reached-success episodes",
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+ "task_efficiency": "benchmark-specific expert-normalized speed ratio: expert_time_s / time_to_stable_success_s over reached-success episodes",
21
+ "avg_steps_to_success": "diagnostic mean steps_to_stable_success over reached-success episodes, or None if no episode succeeds",
22
+ "avg_policy_steps_to_success": "diagnostic mean policy-rate control/action steps through stable success over reached-success episodes",
23
+ "avg_policy_queries_to_success": "diagnostic mean actual model inference queries through stable success over reached-success episodes; None when the first-success query count was not observed",
24
+ "safe_success_rate": "episode success rate with no task-level hard safety violation (drop or tracked-object high speed; joint limits are diagnostic by default)",
25
+ "hard_violation_rate": "episode rate with any task-level hard safety violation (drop or tracked-object high speed; joint limits are diagnostic by default)",
26
+ "drop_rate": "episode rate with drop_off_table or drop_to_table_after_lift violation",
27
+ "high_speed_violation_rate": "episode rate with any tracked object exceeding the configured speed threshold",
28
+ "excessive_impact_rate": "deprecated contact-force impact metric; no longer populated by core safety",
29
+ "robot_constraint_violation_rate": "diagnostic episode rate with any asset hard-joint-limit observation; excluded from safe_success_rate unless include_in_core_safety is explicitly enabled",
30
+ "finger_joint_limit_saturation_rate": "episode rate with dexterous finger joints saturated beyond finger joint-limit thresholds; diagnostic by default and not included in safe_success_rate",
31
+ "joint_limit_active_step_rate": "diagnostic mean fraction of steps with any joint exceeding the soft diagnostic margin",
32
+ "finger_joint_limit_saturation_step_rate": "diagnostic mean fraction of steps with finger joint-limit saturation",
33
+ "max_joint_limit_excess_rad": "diagnostic maximum operating/soft-limit excess observed in radians; hard-limit source and role validation are in robot_constraint_diagnostics",
34
+ "safety_violation_rate_time": "compatibility diagnostic; with fixed physics_dt this is equivalent to safety_violation_step_rate and is omitted from grouped summary output",
35
+ "safety_violation_step_rate": "core safety metric: fraction of executed steps with task-level safety violations; joint-limit observations are excluded by default",
36
+ "safety_violation_rate_event": "deprecated compatibility alias of safety_violation_events_per_step; omitted from grouped summary output",
37
+ "safety_violation_events_per_step": "diagnostic event density; may exceed 1 when multiple violations happen in one step",
38
+ "episode_violation_rate": "compatibility alias of hard_violation_rate; omitted from grouped core output",
39
+ "latched_stage_completion_rate": "main progress metric; ever-reached stage completion rate at episode end",
40
+ "current_stage_completion_rate": "diagnostic terminal-state stage completion rate at episode end",
41
+ "current_normalized_progress_score": "chain-depth diagnostic; normalized progress score at episode end",
42
+ "current_chain_depth_progress_score": "alias of current_normalized_progress_score for ordered dependency-depth diagnostics",
43
+ "latched_chain_depth_progress_score": "alias of latched_normalized_progress_score for ever-reached dependency-depth diagnostics",
44
+ "robustness": "success rates grouped by benchmark protocol category: cov, inv, and inv+cov"
45
+ }
46
+ },
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+ "core_metrics": {
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+ "completion": {
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+ "success_rate_ci": {
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54
+ }
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+ },
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+ },
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+ "hard_violation_rate": 0.9,
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+ "high_speed_violation_rate": 0.3,
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+ "task_family_success_rate": {
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+ }
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+ "avg_latched_chain_depth": 1.4
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+ },
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+ "efficiency": {
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+ "expert_time_s": 20.05,
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+ "expert_time_step": 1203,
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+ "avg_policy_queries_to_success": null
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+ },
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+ "violation_counts": {
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+ "drop_obj_014_lemon_3": 1,
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+ "drop_obj_017_orange_4": 2,
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+ "drop_to_table_obj_014_lemon_2": 3,
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+ "drop_to_table_obj_014_lemon_3": 1,
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+ "drop_to_table_obj_017_orange_4": 9,
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+ "drop_to_table_obj_017_orange_5": 3,
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+ "high_speed_obj_014_lemon_2": 2,
105
+ "high_speed_obj_014_lemon_3": 1,
106
+ "high_speed_obj_017_orange_4": 2,
107
+ "high_speed_obj_029_plate_1": 1
108
+ },
109
+ "robot_constraint_violation_rate": 0.9,
110
+ "finger_joint_limit_saturation_rate": 0.6,
111
+ "joint_limit_active_step_rate": 0.053005464480874315,
112
+ "finger_joint_limit_saturation_step_rate": 0.009653916211293261,
113
+ "max_joint_limit_excess_rad": 1.5978164672851562,
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+ "robot_constraint_diagnostics": {
115
+ "joint_limit_soft_counts": {
116
+ "left_index_dip_joint": 11,
117
+ "left_index_mcp_joint": 4,
118
+ "left_index_pip_joint": 16,
119
+ "left_middle_dip_joint": 35,
120
+ "left_middle_mcp_joint": 29,
121
+ "left_middle_pip_joint": 73,
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+ "left_middle_pitch_joint": 17,
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+ "left_pinky_mcp_joint": 92,
124
+ "left_pinky_pip_joint": 37,
125
+ "left_ring_dip_joint": 23,
126
+ "left_ring_mcp_joint": 46,
127
+ "left_ring_pip_joint": 52,
128
+ "left_thumb_dip_joint": 21,
129
+ "left_thumb_mcp_joint": 358,
130
+ "left_thumb_pip_joint": 1,
131
+ "left_thumb_yaw_joint": 52,
132
+ "right_index_pip_joint": 2,
133
+ "right_middle_pip_joint": 7,
134
+ "right_ring_pip_joint": 3,
135
+ "right_thumb_mcp_joint": 250
136
+ },
137
+ "joint_limit_hard_counts": {
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139
+ "left_index_mcp_joint": 1,
140
+ "left_index_pip_joint": 32,
141
+ "left_middle_dip_joint": 2,
142
+ "left_middle_mcp_joint": 2,
143
+ "left_middle_pip_joint": 133,
144
+ "left_middle_pitch_joint": 1,
145
+ "left_pinky_dip_joint": 1,
146
+ "left_pinky_mcp_joint": 9,
147
+ "left_pinky_pip_joint": 3,
148
+ "left_ring_dip_joint": 2,
149
+ "left_ring_mcp_joint": 4,
150
+ "left_ring_pip_joint": 10,
151
+ "left_thumb_dip_joint": 2,
152
+ "left_thumb_mcp_joint": 30,
153
+ "left_thumb_pip_joint": 1,
154
+ "left_thumb_yaw_joint": 2,
155
+ "right_index_pip_joint": 30,
156
+ "right_middle_pip_joint": 72,
157
+ "right_ring_pip_joint": 2,
158
+ "right_thumb_mcp_joint": 27
159
+ },
160
+ "joint_limit_hard_episode_events": 220,
161
+ "finger_joint_limit_saturation_counts": {
162
+ "left_index_dip_joint": 6,
163
+ "left_middle_dip_joint": 29,
164
+ "left_middle_mcp_joint": 15,
165
+ "left_pinky_mcp_joint": 6,
166
+ "left_pinky_pip_joint": 26,
167
+ "left_ring_dip_joint": 11,
168
+ "left_ring_mcp_joint": 23,
169
+ "left_ring_pip_joint": 25,
170
+ "left_thumb_dip_joint": 12,
171
+ "left_thumb_mcp_joint": 44,
172
+ "left_thumb_yaw_joint": 44,
173
+ "right_thumb_mcp_joint": 10
174
+ },
175
+ "joint_limit_max_excess_by_joint": {
176
+ "left_index_dip_joint": 0.40528249740600586,
177
+ "left_index_mcp_joint": 0.06639307737350464,
178
+ "left_index_pip_joint": 0.14446650445461273,
179
+ "left_index_pitch_joint": 0.0033638954628258944,
180
+ "left_middle_dip_joint": 1.5978164672851562,
181
+ "left_middle_mcp_joint": 0.6392132043838501,
182
+ "left_middle_pip_joint": 0.2057327926158905,
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+ "left_middle_pitch_joint": 0.03984842076897621,
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+ "left_pinky_dip_joint": 0.006871405057609081,
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+ "left_pinky_mcp_joint": 0.28638166189193726,
186
+ "left_pinky_pip_joint": 1.280145525932312,
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+ "left_ring_dip_joint": 0.534247875213623,
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+ "left_ring_mcp_joint": 0.7535475492477417,
189
+ "left_ring_pip_joint": 0.8452719449996948,
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+ "left_thumb_dip_joint": 0.7821993231773376,
191
+ "left_thumb_mcp_joint": 0.6103029251098633,
192
+ "left_thumb_pip_joint": 0.017655611038208008,
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+ "left_thumb_yaw_joint": 0.7936220169067383,
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+ "right_index_dip_joint": 5.028687519370578e-05,
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+ "right_index_pip_joint": 0.052236296236515045,
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+ "right_index_pitch_joint": 0.00014959948020987213,
197
+ "right_middle_dip_joint": 0.0003015365800820291,
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+ "right_middle_pip_joint": 0.19331547617912292,
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+ "right_middle_pitch_joint": 0.0002718656905926764,
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+ "right_pinky_dip_joint": 0.00038979147211648524,
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+ "right_pinky_mcp_joint": 0.0006187328253872693,
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+ "right_pinky_pip_joint": 0.0008713925490155816,
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+ "right_ring_dip_joint": 0.00021358171943575144,
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+ "right_ring_mcp_joint": 0.0001470772986067459,
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+ "right_ring_pip_joint": 0.03229715675115585,
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+ "right_thumb_dip_joint": 2.9477143471012823e-05,
207
+ "right_thumb_mcp_joint": 0.29763340950012207,
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+ "right_thumb_pip_joint": 4.7241366701200604e-05,
209
+ "right_thumb_yaw_joint": 1.998916657197647e-11
210
+ },
211
+ "coverage": {
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+ "hard_limit_source": {
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+ "available": 10,
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+ "unavailable": 0,
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+ "unknown": 0
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+ },
217
+ "joint_role_manifest": {
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+ "available": 10,
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+ "unavailable": 0,
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+ "unknown": 0
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+ }
222
+ },
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+ "hard_limit_sources": {
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+ "runtime.joint_pos_limits": 10
225
+ },
226
+ "soft_limit_sources": {
227
+ "runtime.soft_joint_pos_limits": 10
228
+ },
229
+ "unknown_runtime_joint_names": [],
230
+ "baseline_checks": {
231
+ "post_home": {
232
+ "checked": 10,
233
+ "hard_violation_episodes": 0
234
+ },
235
+ "post_reset": {
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+ "checked": 10,
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+ "hard_violation_episodes": 0
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+ }
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+ }
240
+ }
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+ },
242
+ "robot_motion": {
243
+ "joint_acceleration_rms": 24.961714088569405,
244
+ "joint_effort_rms": 32.44377230761677,
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+ "joint_jerk_rms": 2483.7157956358647,
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+ "joint_velocity_rms": 0.5874940997851043
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+ },
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+ "grasp": {
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+ "kinematic_grasp_stability_index": 0.8622755407368967,
250
+ "mean_kinematic_grasp_stability": 0.41917867169956197,
251
+ "per_object_best_kinematic_grasp_stability": {
252
+ "obj_014_lemon_2": 0.7741835969714579,
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+ "obj_014_lemon_3": 0.7023812118533483,
254
+ "obj_017_orange_4": 0.4459987070772581,
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+ "obj_017_orange_5": 0.3496105877623669
256
+ },
257
+ "grasp_gsi_diagnostics": {
258
+ "mean_anti_slip_score": 0.7558600959763804,
259
+ "mean_duration_score": 0.33843992248061877,
260
+ "mean_hold_score": 0.20455287929125243,
261
+ "mean_kinematic_stability_score": 0.05351032437012617,
262
+ "mean_legacy_gsi": 0.3464732089348715,
263
+ "mean_lift_score": 0.2882613510520487,
264
+ "mean_motion_stability_score": 0.20219920816885556
265
+ }
266
+ },
267
+ "tool": {
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+ "tool_selection_accuracy": null,
269
+ "tool_switch_success_rate": null,
270
+ "tool_switch_total": 0,
271
+ "tool_switch_successful": 0
272
+ },
273
+ "runtime": {
274
+ "avg_steps": 1647,
275
+ "error_count": 1
276
+ }
277
+ }
278
+ }
gpt6_astra_1x_icl/per_task_eval/08_frypan_stand_pour/Full/per_episode.jsonl ADDED
The diff for this file is too large to render. See raw diff
 
gpt6_astra_1x_icl/per_task_eval/08_frypan_stand_pour/Full/summary.json ADDED
@@ -0,0 +1,307 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "metric_schema_version": "core-v1.8-policy-step-query-split",
3
+ "metadata": {
4
+ "policy_name": "gpt-6-astra",
5
+ "base_seed": 200800000,
6
+ "seed_policy": "episode_seed = base_seed + episode_index - 1",
7
+ "randomization_recorded": true,
8
+ "n_episodes": 10,
9
+ "successes": 0,
10
+ "error_count": 1,
11
+ "evaluation_protocol": "reach_and_stop",
12
+ "early_stop": true,
13
+ "success_definition": "terminal.raw_condition holds for dwell_time_s",
14
+ "measurement_window": "episode_start_to_stable_success_or_failure_budget",
15
+ "max_episode_steps": 3432,
16
+ "dwell_time_s": 0.5,
17
+ "field_semantics": {
18
+ "success_rate": "primary protocol success rate: stable_success for reach_and_stop; terminal at_end_success_budget for fixed_horizon",
19
+ "avg_time_to_success_s": "main efficiency metric: mean time_to_stable_success_s over reached-success episodes",
20
+ "task_efficiency": "benchmark-specific expert-normalized speed ratio: expert_time_s / time_to_stable_success_s over reached-success episodes",
21
+ "avg_steps_to_success": "diagnostic mean steps_to_stable_success over reached-success episodes, or None if no episode succeeds",
22
+ "avg_policy_steps_to_success": "diagnostic mean policy-rate control/action steps through stable success over reached-success episodes",
23
+ "avg_policy_queries_to_success": "diagnostic mean actual model inference queries through stable success over reached-success episodes; None when the first-success query count was not observed",
24
+ "safe_success_rate": "episode success rate with no task-level hard safety violation (drop or tracked-object high speed; joint limits are diagnostic by default)",
25
+ "hard_violation_rate": "episode rate with any task-level hard safety violation (drop or tracked-object high speed; joint limits are diagnostic by default)",
26
+ "drop_rate": "episode rate with drop_off_table or drop_to_table_after_lift violation",
27
+ "high_speed_violation_rate": "episode rate with any tracked object exceeding the configured speed threshold",
28
+ "excessive_impact_rate": "deprecated contact-force impact metric; no longer populated by core safety",
29
+ "robot_constraint_violation_rate": "diagnostic episode rate with any asset hard-joint-limit observation; excluded from safe_success_rate unless include_in_core_safety is explicitly enabled",
30
+ "finger_joint_limit_saturation_rate": "episode rate with dexterous finger joints saturated beyond finger joint-limit thresholds; diagnostic by default and not included in safe_success_rate",
31
+ "joint_limit_active_step_rate": "diagnostic mean fraction of steps with any joint exceeding the soft diagnostic margin",
32
+ "finger_joint_limit_saturation_step_rate": "diagnostic mean fraction of steps with finger joint-limit saturation",
33
+ "max_joint_limit_excess_rad": "diagnostic maximum operating/soft-limit excess observed in radians; hard-limit source and role validation are in robot_constraint_diagnostics",
34
+ "safety_violation_rate_time": "compatibility diagnostic; with fixed physics_dt this is equivalent to safety_violation_step_rate and is omitted from grouped summary output",
35
+ "safety_violation_step_rate": "core safety metric: fraction of executed steps with task-level safety violations; joint-limit observations are excluded by default",
36
+ "safety_violation_rate_event": "deprecated compatibility alias of safety_violation_events_per_step; omitted from grouped summary output",
37
+ "safety_violation_events_per_step": "diagnostic event density; may exceed 1 when multiple violations happen in one step",
38
+ "episode_violation_rate": "compatibility alias of hard_violation_rate; omitted from grouped core output",
39
+ "latched_stage_completion_rate": "main progress metric; ever-reached stage completion rate at episode end",
40
+ "current_stage_completion_rate": "diagnostic terminal-state stage completion rate at episode end",
41
+ "current_normalized_progress_score": "chain-depth diagnostic; normalized progress score at episode end",
42
+ "current_chain_depth_progress_score": "alias of current_normalized_progress_score for ordered dependency-depth diagnostics",
43
+ "latched_chain_depth_progress_score": "alias of latched_normalized_progress_score for ever-reached dependency-depth diagnostics",
44
+ "robustness": "success rates grouped by benchmark protocol category: cov, inv, and inv+cov"
45
+ }
46
+ },
47
+ "core_metrics": {
48
+ "completion": {
49
+ "success_rate": 0.0,
50
+ "success_rate_ci": {
51
+ "mean": 0.0,
52
+ "ci_low": 0.0,
53
+ "ci_high": 0.0
54
+ }
55
+ },
56
+ "progress": {
57
+ "latched_stage_completion_rate": 0.15
58
+ },
59
+ "efficiency": {
60
+ "avg_time_to_success_s": null
61
+ },
62
+ "safety": {
63
+ "safe_success_rate": 0.0,
64
+ "hard_violation_rate": 0.3,
65
+ "drop_rate": 0.0,
66
+ "high_speed_violation_rate": 0.3,
67
+ "safety_violation_step_rate": 0.00032802528776763884
68
+ },
69
+ "robustness": {}
70
+ },
71
+ "diagnostic_metrics": {
72
+ "completion": {
73
+ "ever_instant_success_rate": 0.0,
74
+ "at_end_success_rate": 0.0,
75
+ "task_family_success_rate": {
76
+ "pour_tilt": 0.0
77
+ }
78
+ },
79
+ "progress": {
80
+ "current_stage_completion_rate": 0.0,
81
+ "current_chain_depth_progress_score": 0.0,
82
+ "latched_chain_depth_progress_score": 0.3,
83
+ "avg_current_chain_depth": 0,
84
+ "avg_latched_chain_depth": 0.3
85
+ },
86
+ "efficiency": {
87
+ "task_efficiency": null,
88
+ "expert_time_s": 38.13333333333333,
89
+ "expert_time_step": 2288,
90
+ "avg_steps_to_success": null,
91
+ "avg_policy_steps_to_success": null,
92
+ "avg_policy_queries_to_success": null
93
+ },
94
+ "safety": {
95
+ "safety_violation_events_per_step": 8.946144211844694e-05,
96
+ "violation_counts": {
97
+ "high_speed_obj_172_soy_sauce_1": 1,
98
+ "high_speed_obj_182_bread_2": 2
99
+ },
100
+ "robot_constraint_violation_rate": 1.0,
101
+ "finger_joint_limit_saturation_rate": 1.0,
102
+ "joint_limit_active_step_rate": 0.10458042583646449,
103
+ "finger_joint_limit_saturation_step_rate": 0.0571062205522753,
104
+ "max_joint_limit_excess_rad": 2.122424602508545,
105
+ "robot_constraint_diagnostics": {
106
+ "joint_limit_soft_counts": {
107
+ "left_hand_Finger_Spread": 285,
108
+ "left_hand_Index_Finger_Distal": 422,
109
+ "left_hand_Index_Finger_Proximal": 629,
110
+ "left_hand_Middle_Finger_Distal": 208,
111
+ "left_hand_Middle_Finger_Proximal": 474,
112
+ "left_hand_Pinky": 261,
113
+ "left_hand_Ring_Finger": 276,
114
+ "left_hand_Thumb_Flexion": 1534,
115
+ "left_hand_Thumb_Opposition": 238,
116
+ "left_hand_index_spread": 265,
117
+ "left_hand_j12": 214,
118
+ "left_hand_j13": 210,
119
+ "left_hand_j14": 14,
120
+ "left_hand_j15": 3,
121
+ "left_hand_j16": 6,
122
+ "left_hand_j17": 41,
123
+ "left_hand_j3": 574,
124
+ "left_hand_j4": 2,
125
+ "left_hand_j5": 402,
126
+ "left_hand_ring_spread": 388,
127
+ "right_hand_Index_Finger_Distal": 62,
128
+ "right_hand_Index_Finger_Proximal": 64,
129
+ "right_hand_Middle_Finger_Distal": 105,
130
+ "right_hand_Middle_Finger_Proximal": 299,
131
+ "right_hand_Pinky": 76,
132
+ "right_hand_Ring_Finger": 181,
133
+ "right_hand_Thumb_Flexion": 105,
134
+ "right_hand_j12": 15,
135
+ "right_hand_j13": 92,
136
+ "right_hand_j15": 101,
137
+ "right_hand_j3": 159
138
+ },
139
+ "joint_limit_hard_counts": {
140
+ "left_hand_Finger_Spread": 19,
141
+ "left_hand_Index_Finger_Distal": 13,
142
+ "left_hand_Index_Finger_Proximal": 30,
143
+ "left_hand_Middle_Finger_Distal": 11,
144
+ "left_hand_Middle_Finger_Proximal": 22,
145
+ "left_hand_Pinky": 10,
146
+ "left_hand_Ring_Finger": 16,
147
+ "left_hand_Thumb_Flexion": 35,
148
+ "left_hand_Thumb_Opposition": 18,
149
+ "left_hand_index_spread": 47,
150
+ "left_hand_j12": 10,
151
+ "left_hand_j13": 12,
152
+ "left_hand_j14": 1,
153
+ "left_hand_j15": 1,
154
+ "left_hand_j16": 3,
155
+ "left_hand_j17": 2,
156
+ "left_hand_j3": 21,
157
+ "left_hand_j4": 3,
158
+ "left_hand_j5": 62,
159
+ "left_hand_ring_spread": 12,
160
+ "right_hand_Index_Finger_Distal": 25,
161
+ "right_hand_Index_Finger_Proximal": 18,
162
+ "right_hand_Middle_Finger_Distal": 27,
163
+ "right_hand_Middle_Finger_Proximal": 48,
164
+ "right_hand_Pinky": 22,
165
+ "right_hand_Ring_Finger": 25,
166
+ "right_hand_Thumb_Flexion": 18,
167
+ "right_hand_j12": 16,
168
+ "right_hand_j13": 26,
169
+ "right_hand_j14": 2,
170
+ "right_hand_j15": 3,
171
+ "right_hand_j3": 19,
172
+ "right_hand_j5": 1
173
+ },
174
+ "joint_limit_hard_episode_events": 180,
175
+ "finger_joint_limit_saturation_counts": {
176
+ "left_hand_Finger_Spread": 198,
177
+ "left_hand_Index_Finger_Distal": 316,
178
+ "left_hand_Index_Finger_Proximal": 442,
179
+ "left_hand_Middle_Finger_Distal": 156,
180
+ "left_hand_Middle_Finger_Proximal": 314,
181
+ "left_hand_Pinky": 150,
182
+ "left_hand_Ring_Finger": 88,
183
+ "left_hand_Thumb_Flexion": 647,
184
+ "left_hand_Thumb_Opposition": 147,
185
+ "left_hand_index_spread": 86,
186
+ "left_hand_j12": 159,
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+ "left_hand_j13": 134,
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+ "left_hand_j14": 8,
189
+ "left_hand_j17": 22,
190
+ "left_hand_j3": 363,
191
+ "left_hand_j5": 138,
192
+ "left_hand_ring_spread": 300,
193
+ "right_hand_Middle_Finger_Distal": 62,
194
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+ },
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+ "runtime.soft_joint_pos_limits": 10
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+ },
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+ "unknown_runtime_joint_names": [],
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+ "baseline_checks": {
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+ }
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+ }
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+ },
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+ "per_object_best_kinematic_grasp_stability": {
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+ }
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+ },
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+ "tool": {
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+ "tool_switch_successful": 0
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+ "runtime": {
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+ "error_count": 1
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+ }
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+ }
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gpt6_astra_1x_icl/per_task_eval/09_cleaner_moisturizer_box_loading/Full/per_episode.jsonl ADDED
The diff for this file is too large to render. See raw diff
 
gpt6_astra_1x_icl/per_task_eval/09_cleaner_moisturizer_box_loading/Full/summary.json ADDED
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1
+ {
2
+ "metric_schema_version": "core-v1.8-policy-step-query-split",
3
+ "metadata": {
4
+ "policy_name": "gpt-6-astra",
5
+ "base_seed": 200900000,
6
+ "seed_policy": "episode_seed = base_seed + episode_index - 1",
7
+ "randomization_recorded": true,
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+ "n_episodes": 10,
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+ "successes": 2,
10
+ "error_count": 0,
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+ "early_stop": true,
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+ "success_definition": "terminal.raw_condition holds for dwell_time_s",
14
+ "measurement_window": "episode_start_to_stable_success_or_failure_budget",
15
+ "max_episode_steps": 1926,
16
+ "dwell_time_s": 0.5,
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+ "field_semantics": {
18
+ "success_rate": "primary protocol success rate: stable_success for reach_and_stop; terminal at_end_success_budget for fixed_horizon",
19
+ "avg_time_to_success_s": "main efficiency metric: mean time_to_stable_success_s over reached-success episodes",
20
+ "task_efficiency": "benchmark-specific expert-normalized speed ratio: expert_time_s / time_to_stable_success_s over reached-success episodes",
21
+ "avg_steps_to_success": "diagnostic mean steps_to_stable_success over reached-success episodes, or None if no episode succeeds",
22
+ "avg_policy_steps_to_success": "diagnostic mean policy-rate control/action steps through stable success over reached-success episodes",
23
+ "avg_policy_queries_to_success": "diagnostic mean actual model inference queries through stable success over reached-success episodes; None when the first-success query count was not observed",
24
+ "safe_success_rate": "episode success rate with no task-level hard safety violation (drop or tracked-object high speed; joint limits are diagnostic by default)",
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+ "hard_violation_rate": "episode rate with any task-level hard safety violation (drop or tracked-object high speed; joint limits are diagnostic by default)",
26
+ "drop_rate": "episode rate with drop_off_table or drop_to_table_after_lift violation",
27
+ "high_speed_violation_rate": "episode rate with any tracked object exceeding the configured speed threshold",
28
+ "excessive_impact_rate": "deprecated contact-force impact metric; no longer populated by core safety",
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+ "robot_constraint_violation_rate": "diagnostic episode rate with any asset hard-joint-limit observation; excluded from safe_success_rate unless include_in_core_safety is explicitly enabled",
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+ "finger_joint_limit_saturation_rate": "episode rate with dexterous finger joints saturated beyond finger joint-limit thresholds; diagnostic by default and not included in safe_success_rate",
31
+ "joint_limit_active_step_rate": "diagnostic mean fraction of steps with any joint exceeding the soft diagnostic margin",
32
+ "finger_joint_limit_saturation_step_rate": "diagnostic mean fraction of steps with finger joint-limit saturation",
33
+ "max_joint_limit_excess_rad": "diagnostic maximum operating/soft-limit excess observed in radians; hard-limit source and role validation are in robot_constraint_diagnostics",
34
+ "safety_violation_rate_time": "compatibility diagnostic; with fixed physics_dt this is equivalent to safety_violation_step_rate and is omitted from grouped summary output",
35
+ "safety_violation_step_rate": "core safety metric: fraction of executed steps with task-level safety violations; joint-limit observations are excluded by default",
36
+ "safety_violation_rate_event": "deprecated compatibility alias of safety_violation_events_per_step; omitted from grouped summary output",
37
+ "safety_violation_events_per_step": "diagnostic event density; may exceed 1 when multiple violations happen in one step",
38
+ "episode_violation_rate": "compatibility alias of hard_violation_rate; omitted from grouped core output",
39
+ "latched_stage_completion_rate": "main progress metric; ever-reached stage completion rate at episode end",
40
+ "current_stage_completion_rate": "diagnostic terminal-state stage completion rate at episode end",
41
+ "current_normalized_progress_score": "chain-depth diagnostic; normalized progress score at episode end",
42
+ "current_chain_depth_progress_score": "alias of current_normalized_progress_score for ordered dependency-depth diagnostics",
43
+ "latched_chain_depth_progress_score": "alias of latched_normalized_progress_score for ever-reached dependency-depth diagnostics",
44
+ "robustness": "success rates grouped by benchmark protocol category: cov, inv, and inv+cov"
45
+ }
46
+ },
47
+ "core_metrics": {
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+ "completion": {
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+ "success_rate": 0.2,
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+ "ci_high": 0.5
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+ }
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+ "efficiency": {
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+ "safety": {
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+ "safe_success_rate": 0.2,
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+ "hard_violation_rate": 0.3,
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+ "drop_rate": 0.3,
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+ "high_speed_violation_rate": 0.1,
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+ "task_family_success_rate": {
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+ "latched_chain_depth_progress_score": 0.0,
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+ "avg_current_chain_depth": 0,
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+ "avg_latched_chain_depth": 0
85
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+ "violation_counts": {
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+ "drop_to_table_obj_200_cleaner_2": 3,
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+ "high_speed_obj_154_wooden_box_1": 1
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+ "robot_constraint_violation_rate": 1.0,
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+ "finger_joint_limit_saturation_rate": 0.9,
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+ "joint_limit_active_step_rate": 0.08853533484856493,
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+ "max_joint_limit_excess_rad": 1.7215934991836548,
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+ "joint_limit_soft_counts": {
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+ "joint_limit_hard_episode_events": 135,
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+ "finger_joint_limit_saturation_counts": {
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+ "leap_l_2": 149,
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+ "joint_limit_max_excess_by_joint": {
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+ "joint7": 0.002178192138671875,
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+ "leap_l_10": 1.7215934991836548,
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+ "hard_limit_sources": {
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+ "runtime.joint_pos_limits": 10
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+ "soft_limit_sources": {
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+ "runtime.soft_joint_pos_limits": 10
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+ },
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+ "unknown_runtime_joint_names": [],
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+ "baseline_checks": {
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+ },
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+ "robot_motion": {
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+ "joint_effort_rms": 62.29403347460127,
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+ "joint_jerk_rms": 2366.79009938777,
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+ "per_object_best_kinematic_grasp_stability": {
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+ "obj_200_cleaner_2": 0.8438837776737047,
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+ "obj_209_soap_3": 0.2996346957430446
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+ "grasp_gsi_diagnostics": {
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+ "mean_duration_score": 0.34143576379041307,
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+ "mean_hold_score": 0.2573252645977591,
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+ "mean_legacy_gsi": 0.36872778290899044,
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+ "mean_lift_score": 0.29982892424063234,
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+ "mean_motion_stability_score": 0.23394034772178426
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+ }
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+ },
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+ "tool": {
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+ "tool_switch_success_rate": null,
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+ "tool_switch_total": 0,
230
+ "tool_switch_successful": 0
231
+ },
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+ "runtime": {
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234
+ "error_count": 0
235
+ }
236
+ }
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+ }
gpt6_astra_1x_icl/per_task_eval/12_screwdriver_box_and_hammer/Full/per_episode.jsonl ADDED
The diff for this file is too large to render. See raw diff
 
gpt6_astra_1x_icl/per_task_eval/12_screwdriver_box_and_hammer/Full/summary.json ADDED
@@ -0,0 +1,247 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "metric_schema_version": "core-v1.8-policy-step-query-split",
3
+ "metadata": {
4
+ "policy_name": "gpt-6-astra",
5
+ "base_seed": 201200000,
6
+ "seed_policy": "episode_seed = base_seed + episode_index - 1",
7
+ "randomization_recorded": true,
8
+ "n_episodes": 10,
9
+ "successes": 4,
10
+ "error_count": 1,
11
+ "evaluation_protocol": "reach_and_stop",
12
+ "early_stop": true,
13
+ "success_definition": "terminal.raw_condition holds for dwell_time_s",
14
+ "measurement_window": "episode_start_to_stable_success_or_failure_budget",
15
+ "max_episode_steps": 3447,
16
+ "dwell_time_s": 0.5,
17
+ "field_semantics": {
18
+ "success_rate": "primary protocol success rate: stable_success for reach_and_stop; terminal at_end_success_budget for fixed_horizon",
19
+ "avg_time_to_success_s": "main efficiency metric: mean time_to_stable_success_s over reached-success episodes",
20
+ "task_efficiency": "benchmark-specific expert-normalized speed ratio: expert_time_s / time_to_stable_success_s over reached-success episodes",
21
+ "avg_steps_to_success": "diagnostic mean steps_to_stable_success over reached-success episodes, or None if no episode succeeds",
22
+ "avg_policy_steps_to_success": "diagnostic mean policy-rate control/action steps through stable success over reached-success episodes",
23
+ "avg_policy_queries_to_success": "diagnostic mean actual model inference queries through stable success over reached-success episodes; None when the first-success query count was not observed",
24
+ "safe_success_rate": "episode success rate with no task-level hard safety violation (drop or tracked-object high speed; joint limits are diagnostic by default)",
25
+ "hard_violation_rate": "episode rate with any task-level hard safety violation (drop or tracked-object high speed; joint limits are diagnostic by default)",
26
+ "drop_rate": "episode rate with drop_off_table or drop_to_table_after_lift violation",
27
+ "high_speed_violation_rate": "episode rate with any tracked object exceeding the configured speed threshold",
28
+ "excessive_impact_rate": "deprecated contact-force impact metric; no longer populated by core safety",
29
+ "robot_constraint_violation_rate": "diagnostic episode rate with any asset hard-joint-limit observation; excluded from safe_success_rate unless include_in_core_safety is explicitly enabled",
30
+ "finger_joint_limit_saturation_rate": "episode rate with dexterous finger joints saturated beyond finger joint-limit thresholds; diagnostic by default and not included in safe_success_rate",
31
+ "joint_limit_active_step_rate": "diagnostic mean fraction of steps with any joint exceeding the soft diagnostic margin",
32
+ "finger_joint_limit_saturation_step_rate": "diagnostic mean fraction of steps with finger joint-limit saturation",
33
+ "max_joint_limit_excess_rad": "diagnostic maximum operating/soft-limit excess observed in radians; hard-limit source and role validation are in robot_constraint_diagnostics",
34
+ "safety_violation_rate_time": "compatibility diagnostic; with fixed physics_dt this is equivalent to safety_violation_step_rate and is omitted from grouped summary output",
35
+ "safety_violation_step_rate": "core safety metric: fraction of executed steps with task-level safety violations; joint-limit observations are excluded by default",
36
+ "safety_violation_rate_event": "deprecated compatibility alias of safety_violation_events_per_step; omitted from grouped summary output",
37
+ "safety_violation_events_per_step": "diagnostic event density; may exceed 1 when multiple violations happen in one step",
38
+ "episode_violation_rate": "compatibility alias of hard_violation_rate; omitted from grouped core output",
39
+ "latched_stage_completion_rate": "main progress metric; ever-reached stage completion rate at episode end",
40
+ "current_stage_completion_rate": "diagnostic terminal-state stage completion rate at episode end",
41
+ "current_normalized_progress_score": "chain-depth diagnostic; normalized progress score at episode end",
42
+ "current_chain_depth_progress_score": "alias of current_normalized_progress_score for ordered dependency-depth diagnostics",
43
+ "latched_chain_depth_progress_score": "alias of latched_normalized_progress_score for ever-reached dependency-depth diagnostics",
44
+ "robustness": "success rates grouped by benchmark protocol category: cov, inv, and inv+cov"
45
+ }
46
+ },
47
+ "core_metrics": {
48
+ "completion": {
49
+ "success_rate": 0.4,
50
+ "success_rate_ci": {
51
+ "mean": 0.4,
52
+ "ci_low": 0.1,
53
+ "ci_high": 0.7
54
+ }
55
+ },
56
+ "progress": {
57
+ "latched_stage_completion_rate": 0.85
58
+ },
59
+ "efficiency": {
60
+ "avg_time_to_success_s": 52.94166666666494
61
+ },
62
+ "safety": {
63
+ "safe_success_rate": 0.4,
64
+ "hard_violation_rate": 0.2,
65
+ "drop_rate": 0.2,
66
+ "high_speed_violation_rate": 0.1,
67
+ "safety_violation_step_rate": 0.013190515542559279
68
+ },
69
+ "robustness": {}
70
+ },
71
+ "diagnostic_metrics": {
72
+ "completion": {
73
+ "ever_instant_success_rate": 0.8,
74
+ "at_end_success_rate": 0.5,
75
+ "task_family_success_rate": {
76
+ "tool_precision_place": 0.4
77
+ }
78
+ },
79
+ "progress": {
80
+ "current_stage_completion_rate": 0.8,
81
+ "current_chain_depth_progress_score": 0.8,
82
+ "latched_chain_depth_progress_score": 0.85,
83
+ "avg_current_chain_depth": 3.2,
84
+ "avg_latched_chain_depth": 3.4
85
+ },
86
+ "efficiency": {
87
+ "task_efficiency": 0.7246924442871527,
88
+ "expert_time_s": 38.28333333333333,
89
+ "expert_time_step": 2297,
90
+ "avg_steps_to_success": 3176.5,
91
+ "avg_policy_steps_to_success": 1059.25,
92
+ "avg_policy_queries_to_success": 19.25
93
+ },
94
+ "safety": {
95
+ "safety_violation_events_per_step": 0.00015892187400673829,
96
+ "violation_counts": {
97
+ "drop_obj_044_flat_screwdriver_2": 1,
98
+ "drop_to_table_obj_044_flat_screwdriver_2": 1,
99
+ "drop_to_table_obj_048_hammer_3": 1,
100
+ "high_speed_obj_044_flat_screwdriver_2": 1,
101
+ "high_speed_obj_154_wooden_box_1": 1
102
+ },
103
+ "robot_constraint_violation_rate": 1.0,
104
+ "finger_joint_limit_saturation_rate": 0.9,
105
+ "joint_limit_active_step_rate": 0.11515478990528256,
106
+ "finger_joint_limit_saturation_step_rate": 0.07513826203038586,
107
+ "max_joint_limit_excess_rad": 5.223601818084717,
108
+ "robot_constraint_diagnostics": {
109
+ "joint_limit_soft_counts": {
110
+ "left_index_1_joint": 274,
111
+ "left_little_1_joint": 317,
112
+ "left_middle_1_joint": 246,
113
+ "left_ring_1_joint": 306,
114
+ "left_thumb_2_joint": 870,
115
+ "left_thumb_3_joint": 20,
116
+ "left_thumb_4_joint": 5,
117
+ "right_index_1_joint": 936,
118
+ "right_little_1_joint": 77,
119
+ "right_middle_1_joint": 494,
120
+ "right_ring_1_joint": 482,
121
+ "right_thumb_2_joint": 471,
122
+ "right_thumb_3_joint": 119,
123
+ "right_thumb_4_joint": 10
124
+ },
125
+ "joint_limit_hard_counts": {
126
+ "left_index_1_joint": 19,
127
+ "left_little_1_joint": 8,
128
+ "left_middle_1_joint": 9,
129
+ "left_ring_1_joint": 15,
130
+ "left_thumb_2_joint": 25,
131
+ "left_thumb_3_joint": 1,
132
+ "left_thumb_4_joint": 5,
133
+ "right_index_1_joint": 32,
134
+ "right_little_1_joint": 4,
135
+ "right_middle_1_joint": 15,
136
+ "right_ring_1_joint": 9,
137
+ "right_thumb_2_joint": 7,
138
+ "right_thumb_3_joint": 6,
139
+ "right_thumb_4_joint": 4
140
+ },
141
+ "joint_limit_hard_episode_events": 91,
142
+ "finger_joint_limit_saturation_counts": {
143
+ "left_index_1_joint": 62,
144
+ "left_little_1_joint": 223,
145
+ "left_middle_1_joint": 102,
146
+ "left_ring_1_joint": 109,
147
+ "left_thumb_2_joint": 531,
148
+ "right_index_1_joint": 625,
149
+ "right_little_1_joint": 68,
150
+ "right_middle_1_joint": 238,
151
+ "right_ring_1_joint": 341,
152
+ "right_thumb_2_joint": 329,
153
+ "right_thumb_3_joint": 38
154
+ },
155
+ "joint_limit_max_excess_by_joint": {
156
+ "left_index_1_joint": 0.27620208263397217,
157
+ "left_index_2_joint": 1.139794562732277e-06,
158
+ "left_little_1_joint": 5.223601818084717,
159
+ "left_little_2_joint": 0.0018775563221424818,
160
+ "left_middle_1_joint": 0.32757097482681274,
161
+ "left_middle_2_joint": 1.1005318810930476e-05,
162
+ "left_ring_1_joint": 0.7387237548828125,
163
+ "left_ring_2_joint": 0.004270508419722319,
164
+ "left_thumb_1_joint": 2.2825703126727603e-05,
165
+ "left_thumb_2_joint": 0.4792882204055786,
166
+ "left_thumb_3_joint": 0.09909138828516006,
167
+ "left_thumb_4_joint": 0.03685218095779419,
168
+ "right_index_1_joint": 0.9538151621818542,
169
+ "right_index_2_joint": 7.616848506586393e-06,
170
+ "right_little_1_joint": 1.3297919034957886,
171
+ "right_little_2_joint": 3.0642575438832864e-05,
172
+ "right_middle_1_joint": 0.30515244603157043,
173
+ "right_middle_2_joint": 5.51865559828002e-05,
174
+ "right_ring_1_joint": 0.2909194231033325,
175
+ "right_ring_2_joint": 5.6689455959713086e-05,
176
+ "right_thumb_1_joint": 0.0003198256599716842,
177
+ "right_thumb_2_joint": 0.3879449963569641,
178
+ "right_thumb_3_joint": 0.40510305762290955,
179
+ "right_thumb_4_joint": 0.05127860605716705
180
+ },
181
+ "coverage": {
182
+ "hard_limit_source": {
183
+ "available": 10,
184
+ "unavailable": 0,
185
+ "unknown": 0
186
+ },
187
+ "joint_role_manifest": {
188
+ "available": 10,
189
+ "unavailable": 0,
190
+ "unknown": 0
191
+ }
192
+ },
193
+ "hard_limit_sources": {
194
+ "runtime.joint_pos_limits": 10
195
+ },
196
+ "soft_limit_sources": {
197
+ "runtime.soft_joint_pos_limits": 10
198
+ },
199
+ "unknown_runtime_joint_names": [],
200
+ "baseline_checks": {
201
+ "post_home": {
202
+ "checked": 10,
203
+ "hard_violation_episodes": 0
204
+ },
205
+ "post_reset": {
206
+ "checked": 10,
207
+ "hard_violation_episodes": 0
208
+ }
209
+ }
210
+ }
211
+ },
212
+ "robot_motion": {
213
+ "joint_acceleration_rms": 57.26923484351931,
214
+ "joint_effort_rms": 45.39985160217687,
215
+ "joint_jerk_rms": 5931.196605298128,
216
+ "joint_velocity_rms": 1.196371621151782
217
+ },
218
+ "grasp": {
219
+ "kinematic_grasp_stability_index": 0.9977184232259461,
220
+ "mean_kinematic_grasp_stability": 0.45023017764548745,
221
+ "per_object_best_kinematic_grasp_stability": {
222
+ "obj_043_phillips_screwdriver_1": 0.6986435163758,
223
+ "obj_044_flat_screwdriver_2": 0.9947615671029998,
224
+ "obj_048_hammer_3": 0.4458844659441989
225
+ },
226
+ "grasp_gsi_diagnostics": {
227
+ "mean_anti_slip_score": 0.7957915891988776,
228
+ "mean_duration_score": 0.3958068690583115,
229
+ "mean_hold_score": 0.3459987049394094,
230
+ "mean_kinematic_stability_score": 0.15518423436059983,
231
+ "mean_legacy_gsi": 0.45035378089465894,
232
+ "mean_lift_score": 0.4747552273531635,
233
+ "mean_motion_stability_score": 0.33414277492197964
234
+ }
235
+ },
236
+ "tool": {
237
+ "tool_selection_accuracy": 0.0,
238
+ "tool_switch_success_rate": 0.0,
239
+ "tool_switch_total": 40,
240
+ "tool_switch_successful": 0
241
+ },
242
+ "runtime": {
243
+ "avg_steps": 3146.2,
244
+ "error_count": 1
245
+ }
246
+ }
247
+ }
gpt6_astra_1x_icl/per_task_eval/21_condiment_box_loading/Full/per_episode.jsonl ADDED
The diff for this file is too large to render. See raw diff
 
gpt6_astra_1x_icl/per_task_eval/21_condiment_box_loading/Full/summary.json ADDED
@@ -0,0 +1,250 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "metric_schema_version": "core-v1.8-policy-step-query-split",
3
+ "metadata": {
4
+ "policy_name": "gpt-6-astra",
5
+ "base_seed": 202100000,
6
+ "seed_policy": "episode_seed = base_seed + episode_index - 1",
7
+ "randomization_recorded": true,
8
+ "n_episodes": 10,
9
+ "successes": 2,
10
+ "error_count": 1,
11
+ "evaluation_protocol": "reach_and_stop",
12
+ "early_stop": true,
13
+ "success_definition": "terminal.raw_condition holds for dwell_time_s",
14
+ "measurement_window": "episode_start_to_stable_success_or_failure_budget",
15
+ "max_episode_steps": 2481,
16
+ "dwell_time_s": 0.5,
17
+ "field_semantics": {
18
+ "success_rate": "primary protocol success rate: stable_success for reach_and_stop; terminal at_end_success_budget for fixed_horizon",
19
+ "avg_time_to_success_s": "main efficiency metric: mean time_to_stable_success_s over reached-success episodes",
20
+ "task_efficiency": "benchmark-specific expert-normalized speed ratio: expert_time_s / time_to_stable_success_s over reached-success episodes",
21
+ "avg_steps_to_success": "diagnostic mean steps_to_stable_success over reached-success episodes, or None if no episode succeeds",
22
+ "avg_policy_steps_to_success": "diagnostic mean policy-rate control/action steps through stable success over reached-success episodes",
23
+ "avg_policy_queries_to_success": "diagnostic mean actual model inference queries through stable success over reached-success episodes; None when the first-success query count was not observed",
24
+ "safe_success_rate": "episode success rate with no task-level hard safety violation (drop or tracked-object high speed; joint limits are diagnostic by default)",
25
+ "hard_violation_rate": "episode rate with any task-level hard safety violation (drop or tracked-object high speed; joint limits are diagnostic by default)",
26
+ "drop_rate": "episode rate with drop_off_table or drop_to_table_after_lift violation",
27
+ "high_speed_violation_rate": "episode rate with any tracked object exceeding the configured speed threshold",
28
+ "excessive_impact_rate": "deprecated contact-force impact metric; no longer populated by core safety",
29
+ "robot_constraint_violation_rate": "diagnostic episode rate with any asset hard-joint-limit observation; excluded from safe_success_rate unless include_in_core_safety is explicitly enabled",
30
+ "finger_joint_limit_saturation_rate": "episode rate with dexterous finger joints saturated beyond finger joint-limit thresholds; diagnostic by default and not included in safe_success_rate",
31
+ "joint_limit_active_step_rate": "diagnostic mean fraction of steps with any joint exceeding the soft diagnostic margin",
32
+ "finger_joint_limit_saturation_step_rate": "diagnostic mean fraction of steps with finger joint-limit saturation",
33
+ "max_joint_limit_excess_rad": "diagnostic maximum operating/soft-limit excess observed in radians; hard-limit source and role validation are in robot_constraint_diagnostics",
34
+ "safety_violation_rate_time": "compatibility diagnostic; with fixed physics_dt this is equivalent to safety_violation_step_rate and is omitted from grouped summary output",
35
+ "safety_violation_step_rate": "core safety metric: fraction of executed steps with task-level safety violations; joint-limit observations are excluded by default",
36
+ "safety_violation_rate_event": "deprecated compatibility alias of safety_violation_events_per_step; omitted from grouped summary output",
37
+ "safety_violation_events_per_step": "diagnostic event density; may exceed 1 when multiple violations happen in one step",
38
+ "episode_violation_rate": "compatibility alias of hard_violation_rate; omitted from grouped core output",
39
+ "latched_stage_completion_rate": "main progress metric; ever-reached stage completion rate at episode end",
40
+ "current_stage_completion_rate": "diagnostic terminal-state stage completion rate at episode end",
41
+ "current_normalized_progress_score": "chain-depth diagnostic; normalized progress score at episode end",
42
+ "current_chain_depth_progress_score": "alias of current_normalized_progress_score for ordered dependency-depth diagnostics",
43
+ "latched_chain_depth_progress_score": "alias of latched_normalized_progress_score for ever-reached dependency-depth diagnostics",
44
+ "robustness": "success rates grouped by benchmark protocol category: cov, inv, and inv+cov"
45
+ }
46
+ },
47
+ "core_metrics": {
48
+ "completion": {
49
+ "success_rate": 0.2,
50
+ "success_rate_ci": {
51
+ "mean": 0.2,
52
+ "ci_low": 0.0,
53
+ "ci_high": 0.5
54
+ }
55
+ },
56
+ "progress": {
57
+ "latched_stage_completion_rate": 0.23333333333333334
58
+ },
59
+ "efficiency": {
60
+ "avg_time_to_success_s": 40.49166666666565
61
+ },
62
+ "safety": {
63
+ "safe_success_rate": 0.2,
64
+ "hard_violation_rate": 0.5,
65
+ "drop_rate": 0.5,
66
+ "high_speed_violation_rate": 0.0,
67
+ "safety_violation_step_rate": 0.0002968365702654567
68
+ },
69
+ "robustness": {}
70
+ },
71
+ "diagnostic_metrics": {
72
+ "completion": {
73
+ "ever_instant_success_rate": 0.2,
74
+ "at_end_success_rate": 0.2,
75
+ "task_family_success_rate": {
76
+ "rigid_pick_place": 0.2
77
+ }
78
+ },
79
+ "progress": {
80
+ "current_stage_completion_rate": 0.23333333333333334,
81
+ "current_chain_depth_progress_score": 0.25,
82
+ "latched_chain_depth_progress_score": 0.25,
83
+ "avg_current_chain_depth": 0.5,
84
+ "avg_latched_chain_depth": 0.5
85
+ },
86
+ "efficiency": {
87
+ "task_efficiency": 0.6810269994526049,
88
+ "expert_time_s": 27.566666666666666,
89
+ "expert_time_step": 1654,
90
+ "avg_steps_to_success": 2429.5,
91
+ "avg_policy_steps_to_success": 810,
92
+ "avg_policy_queries_to_success": 22.5
93
+ },
94
+ "safety": {
95
+ "safety_violation_events_per_step": 0.0002968365702654567,
96
+ "violation_counts": {
97
+ "drop_to_table_obj_171_msg_4": 5,
98
+ "drop_to_table_obj_172_soy_sauce_2": 2
99
+ },
100
+ "robot_constraint_violation_rate": 0.9,
101
+ "finger_joint_limit_saturation_rate": 0.7,
102
+ "joint_limit_active_step_rate": 0.03290645407514206,
103
+ "finger_joint_limit_saturation_step_rate": 0.020693749469934696,
104
+ "max_joint_limit_excess_rad": 2.4376306533813477,
105
+ "robot_constraint_diagnostics": {
106
+ "joint_limit_soft_counts": {
107
+ "left_finger2_joint4": 47,
108
+ "left_finger3_joint4": 55,
109
+ "left_finger4_joint2": 9,
110
+ "left_finger4_joint4": 55,
111
+ "left_finger5_joint4": 52,
112
+ "right_finger1_joint1": 216,
113
+ "right_finger1_joint2": 244,
114
+ "right_finger1_joint3": 222,
115
+ "right_finger2_joint1": 107,
116
+ "right_finger3_joint1": 53,
117
+ "right_finger3_joint4": 72,
118
+ "right_finger4_joint1": 13,
119
+ "right_finger4_joint2": 20,
120
+ "right_finger4_joint4": 46,
121
+ "right_finger5_joint1": 14,
122
+ "right_finger5_joint2": 27,
123
+ "right_finger5_joint4": 28
124
+ },
125
+ "joint_limit_hard_counts": {
126
+ "left_finger2_joint4": 1,
127
+ "left_finger3_joint4": 1,
128
+ "left_finger4_joint2": 1,
129
+ "left_finger4_joint4": 1,
130
+ "left_finger5_joint4": 1,
131
+ "right_finger1_joint1": 5,
132
+ "right_finger1_joint2": 50,
133
+ "right_finger1_joint3": 11,
134
+ "right_finger2_joint1": 7,
135
+ "right_finger3_joint1": 2,
136
+ "right_finger3_joint4": 2,
137
+ "right_finger4_joint1": 3,
138
+ "right_finger4_joint2": 6,
139
+ "right_finger4_joint4": 3,
140
+ "right_finger5_joint1": 1,
141
+ "right_finger5_joint2": 5,
142
+ "right_finger5_joint4": 1
143
+ },
144
+ "joint_limit_hard_episode_events": 64,
145
+ "finger_joint_limit_saturation_counts": {
146
+ "left_finger2_joint4": 45,
147
+ "left_finger3_joint4": 53,
148
+ "left_finger4_joint4": 53,
149
+ "left_finger5_joint4": 48,
150
+ "right_finger1_joint1": 174,
151
+ "right_finger1_joint2": 137,
152
+ "right_finger1_joint3": 78,
153
+ "right_finger2_joint1": 47,
154
+ "right_finger3_joint1": 12,
155
+ "right_finger3_joint4": 65,
156
+ "right_finger4_joint4": 36,
157
+ "right_finger5_joint2": 10,
158
+ "right_finger5_joint4": 24
159
+ },
160
+ "joint_limit_max_excess_by_joint": {
161
+ "left_finger1_joint2": 0.00391620397567749,
162
+ "left_finger2_joint1": 0.0003159046173095703,
163
+ "left_finger2_joint2": 0.00010144710540771484,
164
+ "left_finger2_joint4": 1.8637301921844482,
165
+ "left_finger3_joint4": 2.3013296127319336,
166
+ "left_finger4_joint2": 0.11612790822982788,
167
+ "left_finger4_joint4": 2.4376306533813477,
168
+ "left_finger5_joint2": 0.0035106539726257324,
169
+ "left_finger5_joint4": 2.2746286392211914,
170
+ "right_finger1_joint1": 1.5812128782272339,
171
+ "right_finger1_joint2": 1.083169937133789,
172
+ "right_finger1_joint3": 0.7230508923530579,
173
+ "right_finger2_joint1": 0.3803626298904419,
174
+ "right_finger2_joint2": 0.0009592175483703613,
175
+ "right_finger3_joint1": 0.1703876256942749,
176
+ "right_finger3_joint4": 1.728808045387268,
177
+ "right_finger4_joint1": 0.018409013748168945,
178
+ "right_finger4_joint2": 0.20231959223747253,
179
+ "right_finger4_joint4": 1.2384870052337646,
180
+ "right_finger5_joint1": 0.23881781101226807,
181
+ "right_finger5_joint2": 0.40025654435157776,
182
+ "right_finger5_joint4": 0.6091189384460449
183
+ },
184
+ "coverage": {
185
+ "hard_limit_source": {
186
+ "available": 10,
187
+ "unavailable": 0,
188
+ "unknown": 0
189
+ },
190
+ "joint_role_manifest": {
191
+ "available": 10,
192
+ "unavailable": 0,
193
+ "unknown": 0
194
+ }
195
+ },
196
+ "hard_limit_sources": {
197
+ "runtime.joint_pos_limits": 10
198
+ },
199
+ "soft_limit_sources": {
200
+ "runtime.soft_joint_pos_limits": 10
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gpt6_astra_1x_icl/per_task_eval/22_tool_box_loading/Full/per_episode.jsonl ADDED
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gpt6_astra_1x_icl/per_task_eval/22_tool_box_loading/Full/summary.json ADDED
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+ {
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+ "seed_policy": "episode_seed = base_seed + episode_index - 1",
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+ "avg_policy_steps_to_success": "diagnostic mean policy-rate control/action steps through stable success over reached-success episodes",
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+ "joint_limit_active_step_rate": "diagnostic mean fraction of steps with any joint exceeding the soft diagnostic margin",
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+ "safety_violation_step_rate": "core safety metric: fraction of executed steps with task-level safety violations; joint-limit observations are excluded by default",
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+ "current_chain_depth_progress_score": "alias of current_normalized_progress_score for ordered dependency-depth diagnostics",
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The diff for this file is too large to render. See raw diff
 
gpt6_astra_1x_icl/per_task_eval/24_stationery_category_sorting/Full/summary.json ADDED
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+ "avg_steps_to_success": "diagnostic mean steps_to_stable_success over reached-success episodes, or None if no episode succeeds",
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+ "avg_policy_steps_to_success": "diagnostic mean policy-rate control/action steps through stable success over reached-success episodes",
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+ "avg_policy_queries_to_success": "diagnostic mean actual model inference queries through stable success over reached-success episodes; None when the first-success query count was not observed",
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+ "high_speed_violation_rate": "episode rate with any tracked object exceeding the configured speed threshold",
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+ "finger_joint_limit_saturation_rate": "episode rate with dexterous finger joints saturated beyond finger joint-limit thresholds; diagnostic by default and not included in safe_success_rate",
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+ "joint_limit_active_step_rate": "diagnostic mean fraction of steps with any joint exceeding the soft diagnostic margin",
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+ "finger_joint_limit_saturation_step_rate": "diagnostic mean fraction of steps with finger joint-limit saturation",
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+ "max_joint_limit_excess_rad": "diagnostic maximum operating/soft-limit excess observed in radians; hard-limit source and role validation are in robot_constraint_diagnostics",
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+ "safety_violation_rate_time": "compatibility diagnostic; with fixed physics_dt this is equivalent to safety_violation_step_rate and is omitted from grouped summary output",
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+ "safety_violation_step_rate": "core safety metric: fraction of executed steps with task-level safety violations; joint-limit observations are excluded by default",
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+ "safety_violation_rate_event": "deprecated compatibility alias of safety_violation_events_per_step; omitted from grouped summary output",
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+ "safety_violation_events_per_step": "diagnostic event density; may exceed 1 when multiple violations happen in one step",
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+ "episode_violation_rate": "compatibility alias of hard_violation_rate; omitted from grouped core output",
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+ "latched_stage_completion_rate": "main progress metric; ever-reached stage completion rate at episode end",
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+ "current_stage_completion_rate": "diagnostic terminal-state stage completion rate at episode end",
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+ "current_normalized_progress_score": "chain-depth diagnostic; normalized progress score at episode end",
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+ "current_chain_depth_progress_score": "alias of current_normalized_progress_score for ordered dependency-depth diagnostics",
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+ "latched_chain_depth_progress_score": "alias of latched_normalized_progress_score for ever-reached dependency-depth diagnostics",
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+ "robustness": "success rates grouped by benchmark protocol category: cov, inv, and inv+cov"
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+ "drop_to_table_obj_168_battery_6": 2,
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+ "right_ring_distal_joint": 816,
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+ "right_thumb_proximal_joint": 13
155
+ },
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157
+ "finger_joint_limit_saturation_counts": {
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+ "left_pinky_distal_joint": 39,
160
+ "left_pinky_proximal_joint": 37,
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+ "left_ring_distal_joint": 99,
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+ "left_thumb_distal_joint": 40,
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+ "right_index_distal_joint": 38,
164
+ "right_index_proximal_joint": 275,
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+ "right_middle_proximal_joint": 445,
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+ "right_pinky_distal_joint": 191,
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+ "right_pinky_proximal_joint": 271,
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+ "right_ring_distal_joint": 442,
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+ "right_ring_proximal_joint": 290,
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+ "right_thumb_distal_joint": 26,
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+ "right_thumb_metacarpal_joint": 225,
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+ "right_thumb_proximal_joint": 15
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+ },
175
+ "joint_limit_max_excess_by_joint": {
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+ "left_index_distal_joint": 0.017278848215937614,
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+ "left_index_proximal_joint": 0.11591135710477829,
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+ "left_middle_distal_joint": 0.011272430419921875,
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+ "left_middle_proximal_joint": 0.028246808797121048,
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+ "left_pinky_proximal_joint": 0.1895831823348999,
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+ "left_ring_proximal_joint": 0.043559636920690536,
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+ "left_thumb_metacarpal_joint": 0.07565286010503769,
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+ "right_index_proximal_joint": 2.296665906906128,
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+ "hard_limit_sources": {
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+ "runtime.joint_pos_limits": 10
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+ },
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+ "soft_limit_sources": {
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+ "runtime.soft_joint_pos_limits": 10
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+ },
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+ "unknown_runtime_joint_names": [],
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+ "baseline_checks": {
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+ "hard_violation_episodes": 0
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+ },
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+ "hard_violation_episodes": 0
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+ "robot_motion": {
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+ "joint_acceleration_rms": 17.79519686065434,
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+ "joint_effort_rms": 44.77046983146167,
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+ "joint_jerk_rms": 1787.0659899737534,
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+ "joint_velocity_rms": 0.4567406371406277
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+ "mean_kinematic_grasp_stability": 0.5321034546628869,
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+ "per_object_best_kinematic_grasp_stability": {
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+ "obj_166_markpen_4": 0.6682970848742789,
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+ "obj_168_battery_6": 0.7739798940890414,
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+ "obj_199_glue_5": 0.7085178799598442,
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+ "obj_221_pen_3": 0.7578735524374395
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+ "grasp_gsi_diagnostics": {
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+ "mean_lift_score": 0.27171962818849976,
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+ "mean_motion_stability_score": 0.18910388950269644
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+ }
254
+ },
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+ "tool": {
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+ "tool_selection_accuracy": null,
257
+ "tool_switch_success_rate": null,
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+ "tool_switch_total": 0,
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+ "tool_switch_successful": 0
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+ },
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+ "runtime": {
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+ "avg_steps": 4626,
263
+ "error_count": 0
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+ }
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+ }
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+ }
gpt6_astra_1x_icl/per_task_eval/26_canned_food_tray_line_arrangement/Full/per_episode.jsonl ADDED
The diff for this file is too large to render. See raw diff
 
gpt6_astra_1x_icl/per_task_eval/26_canned_food_tray_line_arrangement/Full/summary.json ADDED
@@ -0,0 +1,278 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "metric_schema_version": "core-v1.8-policy-step-query-split",
3
+ "metadata": {
4
+ "policy_name": "gpt-6-astra",
5
+ "base_seed": 202600000,
6
+ "seed_policy": "episode_seed = base_seed + episode_index - 1",
7
+ "randomization_recorded": true,
8
+ "n_episodes": 10,
9
+ "successes": 0,
10
+ "error_count": 0,
11
+ "evaluation_protocol": "reach_and_stop",
12
+ "early_stop": true,
13
+ "success_definition": "terminal.raw_condition holds for dwell_time_s",
14
+ "measurement_window": "episode_start_to_stable_success_or_failure_budget",
15
+ "max_episode_steps": 2613,
16
+ "dwell_time_s": 0.5,
17
+ "field_semantics": {
18
+ "success_rate": "primary protocol success rate: stable_success for reach_and_stop; terminal at_end_success_budget for fixed_horizon",
19
+ "avg_time_to_success_s": "main efficiency metric: mean time_to_stable_success_s over reached-success episodes",
20
+ "task_efficiency": "benchmark-specific expert-normalized speed ratio: expert_time_s / time_to_stable_success_s over reached-success episodes",
21
+ "avg_steps_to_success": "diagnostic mean steps_to_stable_success over reached-success episodes, or None if no episode succeeds",
22
+ "avg_policy_steps_to_success": "diagnostic mean policy-rate control/action steps through stable success over reached-success episodes",
23
+ "avg_policy_queries_to_success": "diagnostic mean actual model inference queries through stable success over reached-success episodes; None when the first-success query count was not observed",
24
+ "safe_success_rate": "episode success rate with no task-level hard safety violation (drop or tracked-object high speed; joint limits are diagnostic by default)",
25
+ "hard_violation_rate": "episode rate with any task-level hard safety violation (drop or tracked-object high speed; joint limits are diagnostic by default)",
26
+ "drop_rate": "episode rate with drop_off_table or drop_to_table_after_lift violation",
27
+ "high_speed_violation_rate": "episode rate with any tracked object exceeding the configured speed threshold",
28
+ "excessive_impact_rate": "deprecated contact-force impact metric; no longer populated by core safety",
29
+ "robot_constraint_violation_rate": "diagnostic episode rate with any asset hard-joint-limit observation; excluded from safe_success_rate unless include_in_core_safety is explicitly enabled",
30
+ "finger_joint_limit_saturation_rate": "episode rate with dexterous finger joints saturated beyond finger joint-limit thresholds; diagnostic by default and not included in safe_success_rate",
31
+ "joint_limit_active_step_rate": "diagnostic mean fraction of steps with any joint exceeding the soft diagnostic margin",
32
+ "finger_joint_limit_saturation_step_rate": "diagnostic mean fraction of steps with finger joint-limit saturation",
33
+ "max_joint_limit_excess_rad": "diagnostic maximum operating/soft-limit excess observed in radians; hard-limit source and role validation are in robot_constraint_diagnostics",
34
+ "safety_violation_rate_time": "compatibility diagnostic; with fixed physics_dt this is equivalent to safety_violation_step_rate and is omitted from grouped summary output",
35
+ "safety_violation_step_rate": "core safety metric: fraction of executed steps with task-level safety violations; joint-limit observations are excluded by default",
36
+ "safety_violation_rate_event": "deprecated compatibility alias of safety_violation_events_per_step; omitted from grouped summary output",
37
+ "safety_violation_events_per_step": "diagnostic event density; may exceed 1 when multiple violations happen in one step",
38
+ "episode_violation_rate": "compatibility alias of hard_violation_rate; omitted from grouped core output",
39
+ "latched_stage_completion_rate": "main progress metric; ever-reached stage completion rate at episode end",
40
+ "current_stage_completion_rate": "diagnostic terminal-state stage completion rate at episode end",
41
+ "current_normalized_progress_score": "chain-depth diagnostic; normalized progress score at episode end",
42
+ "current_chain_depth_progress_score": "alias of current_normalized_progress_score for ordered dependency-depth diagnostics",
43
+ "latched_chain_depth_progress_score": "alias of latched_normalized_progress_score for ever-reached dependency-depth diagnostics",
44
+ "robustness": "success rates grouped by benchmark protocol category: cov, inv, and inv+cov"
45
+ }
46
+ },
47
+ "core_metrics": {
48
+ "completion": {
49
+ "success_rate": 0.0,
50
+ "success_rate_ci": {
51
+ "mean": 0.0,
52
+ "ci_low": 0.0,
53
+ "ci_high": 0.0
54
+ }
55
+ },
56
+ "progress": {
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+ "latched_stage_completion_rate": 0.575
58
+ },
59
+ "efficiency": {
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+ "avg_time_to_success_s": null
61
+ },
62
+ "safety": {
63
+ "safe_success_rate": 0.0,
64
+ "hard_violation_rate": 0.1,
65
+ "drop_rate": 0.1,
66
+ "high_speed_violation_rate": 0.0,
67
+ "safety_violation_step_rate": 3.827018752391887e-05
68
+ },
69
+ "robustness": {}
70
+ },
71
+ "diagnostic_metrics": {
72
+ "completion": {
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+ "ever_instant_success_rate": 0.0,
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+ "at_end_success_rate": 0.0,
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+ "task_family_success_rate": {
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+ "rigid_pick_place": 0.0
77
+ }
78
+ },
79
+ "progress": {
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+ "current_stage_completion_rate": 0.4,
81
+ "current_chain_depth_progress_score": 0.6,
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+ "latched_chain_depth_progress_score": 0.8,
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+ "avg_current_chain_depth": 1.2,
84
+ "avg_latched_chain_depth": 1.6
85
+ },
86
+ "efficiency": {
87
+ "task_efficiency": null,
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+ "expert_time_s": 29.03333333333333,
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+ "expert_time_step": 1742,
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+ "avg_steps_to_success": null,
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+ "avg_policy_steps_to_success": null,
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+ "avg_policy_queries_to_success": null
93
+ },
94
+ "safety": {
95
+ "safety_violation_events_per_step": 3.827018752391887e-05,
96
+ "violation_counts": {
97
+ "drop_to_table_obj_002_master_chef_can_2": 1
98
+ },
99
+ "robot_constraint_violation_rate": 0.7,
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+ "finger_joint_limit_saturation_rate": 0.4,
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+ "joint_limit_active_step_rate": 0.017106773823191732,
102
+ "finger_joint_limit_saturation_step_rate": 0.005625717566016073,
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+ "max_joint_limit_excess_rad": 1.7231225967407227,
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+ "robot_constraint_diagnostics": {
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+ "joint_limit_soft_counts": {
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+ "left_index_MCP_FE": 1,
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+ "left_pinky_CMC": 55,
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+ "left_pinky_MCP_FE": 19,
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+ "multi_right_index_DIP": 63,
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+ "multi_right_index_MCP_AA": 52,
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+ "multi_right_index_MCP_FE": 69,
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+ "multi_right_index_PIP": 49,
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+ "multi_right_middle_DIP": 31,
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+ "multi_right_middle_MCP_AA": 56,
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+ "multi_right_middle_MCP_FE": 66,
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+ "multi_right_middle_PIP": 28,
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+ "multi_right_pinky_CMC": 53,
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+ "multi_right_pinky_DIP": 19,
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+ "multi_right_pinky_MCP_AA": 8,
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+ "multi_right_pinky_MCP_FE": 5,
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+ "multi_right_ring_MCP_AA": 23,
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+ "multi_right_ring_MCP_FE": 53,
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+ "multi_right_ring_PIP": 41,
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+ "multi_right_thumb_CMC_AA": 276,
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+ "multi_right_thumb_IP": 49,
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+ "multi_right_thumb_MCP_AA": 50,
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+ "multi_right_thumb_MCP_FE": 19
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+ },
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+ "joint_limit_hard_counts": {
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+ "left_index_MCP_FE": 2,
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+ "left_pinky_CMC": 4,
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+ "left_pinky_MCP_FE": 1,
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+ "multi_right_index_DIP": 2,
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+ "multi_right_index_MCP_AA": 2,
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+ "multi_right_index_MCP_FE": 2,
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+ "multi_right_index_PIP": 2,
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+ "multi_right_middle_DIP": 1,
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+ "multi_right_middle_MCP_AA": 2,
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+ "multi_right_middle_MCP_FE": 2,
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+ "multi_right_middle_PIP": 3,
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+ "multi_right_pinky_CMC": 5,
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+ "multi_right_pinky_DIP": 1,
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+ "multi_right_pinky_MCP_AA": 1,
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+ "multi_right_pinky_MCP_FE": 2,
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+ "multi_right_ring_MCP_AA": 1,
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+ "multi_right_ring_MCP_FE": 2,
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+ "multi_right_ring_PIP": 2,
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+ "multi_right_thumb_CMC_AA": 2,
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+ "multi_right_thumb_IP": 2,
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+ "multi_right_thumb_MCP_AA": 1,
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+ "multi_right_thumb_MCP_FE": 1
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+ },
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+ "joint_limit_hard_episode_events": 13,
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+ "finger_joint_limit_saturation_counts": {
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+ "left_pinky_CMC": 44,
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+ "left_pinky_MCP_FE": 11,
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+ "multi_right_index_DIP": 58,
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+ "multi_right_index_MCP_AA": 28,
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+ "multi_right_index_MCP_FE": 53,
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+ "multi_right_index_PIP": 10,
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+ "multi_right_middle_DIP": 28,
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+ "multi_right_middle_MCP_AA": 41,
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+ "multi_right_middle_MCP_FE": 54,
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+ "multi_right_middle_PIP": 6,
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+ "multi_right_pinky_CMC": 17,
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+ "multi_right_ring_MCP_AA": 18,
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+ "multi_right_ring_MCP_FE": 41,
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+ "multi_right_thumb_MCP_FE": 3
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+ },
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+ "joint_limit_max_excess_by_joint": {
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+ "A5": 1.3828277587890625e-05,
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+ "left_index_MCP_FE": 0.010401219129562378,
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+ "left_index_PIP": 0.00014018648653291166,
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+ "left_middle_PIP": 5.984597737551667e-05,
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+ "left_pinky_CMC": 1.6369332075119019,
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+ "left_pinky_MCP_FE": 0.2908959984779358,
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+ "left_ring_DIP": 5.443812187877484e-05,
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+ "joint_role_manifest": {
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+ "soft_limit_sources": {
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+ "runtime.soft_joint_pos_limits": 10
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+ },
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+ "unknown_runtime_joint_names": [],
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+ "baseline_checks": {
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+ },
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+ "hard_violation_episodes": 0
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+ }
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+ }
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+ }
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+ "robot_motion": {
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+ "joint_effort_rms": 39.6013760297938,
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+ "joint_jerk_rms": 2153.4881366924997,
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+ "joint_velocity_rms": 0.8151944282105695
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+ "grasp": {
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+ "kinematic_grasp_stability_index": 0.9930390387800315,
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+ "mean_kinematic_grasp_stability": 0.5591430792387045,
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+ "per_object_best_kinematic_grasp_stability": {
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+ "obj_002_master_chef_can_2": 0.8581517543203825,
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+ "obj_010_potted_meat_can_5": 0.8543908082115873,
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+ "obj_151_milk_box_4": 0.9615970431595371,
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+ "obj_171_msg_3": 0.9200750754081339
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+ "grasp_gsi_diagnostics": {
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+ "mean_anti_slip_score": 0.8663700727133495,
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+ "mean_duration_score": 0.4545120551090722,
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+ "mean_hold_score": 0.24647292384232733,
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+ "mean_kinematic_stability_score": 0.1433447166025016,
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+ "mean_legacy_gsi": 0.4040219572268817,
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+ "mean_lift_score": 0.28454841178721774,
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+ "mean_motion_stability_score": 0.22292427740378531
265
+ }
266
+ },
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+ "error_count": 0
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+ }
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+ }
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+ }
gpt6_astra_1x_icl/per_task_eval/27_ball_box_loading/Full/per_episode.jsonl ADDED
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gpt6_astra_1x_icl/per_task_eval/27_ball_box_loading/Full/summary.json ADDED
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1
+ {
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+ "metric_schema_version": "core-v1.8-policy-step-query-split",
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+ "metadata": {
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+ "policy_name": "gpt-6-astra",
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+ "base_seed": 202700000,
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+ "seed_policy": "episode_seed = base_seed + episode_index - 1",
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+ "randomization_recorded": true,
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+ "measurement_window": "episode_start_to_stable_success_or_failure_budget",
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+ "max_episode_steps": 3570,
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+ "success_rate": "primary protocol success rate: stable_success for reach_and_stop; terminal at_end_success_budget for fixed_horizon",
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+ "avg_time_to_success_s": "main efficiency metric: mean time_to_stable_success_s over reached-success episodes",
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+ "task_efficiency": "benchmark-specific expert-normalized speed ratio: expert_time_s / time_to_stable_success_s over reached-success episodes",
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+ "avg_steps_to_success": "diagnostic mean steps_to_stable_success over reached-success episodes, or None if no episode succeeds",
22
+ "avg_policy_steps_to_success": "diagnostic mean policy-rate control/action steps through stable success over reached-success episodes",
23
+ "avg_policy_queries_to_success": "diagnostic mean actual model inference queries through stable success over reached-success episodes; None when the first-success query count was not observed",
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+ "safe_success_rate": "episode success rate with no task-level hard safety violation (drop or tracked-object high speed; joint limits are diagnostic by default)",
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+ "hard_violation_rate": "episode rate with any task-level hard safety violation (drop or tracked-object high speed; joint limits are diagnostic by default)",
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+ "drop_rate": "episode rate with drop_off_table or drop_to_table_after_lift violation",
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+ "high_speed_violation_rate": "episode rate with any tracked object exceeding the configured speed threshold",
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+ "excessive_impact_rate": "deprecated contact-force impact metric; no longer populated by core safety",
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+ "robot_constraint_violation_rate": "diagnostic episode rate with any asset hard-joint-limit observation; excluded from safe_success_rate unless include_in_core_safety is explicitly enabled",
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+ "finger_joint_limit_saturation_rate": "episode rate with dexterous finger joints saturated beyond finger joint-limit thresholds; diagnostic by default and not included in safe_success_rate",
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+ "joint_limit_active_step_rate": "diagnostic mean fraction of steps with any joint exceeding the soft diagnostic margin",
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+ "finger_joint_limit_saturation_step_rate": "diagnostic mean fraction of steps with finger joint-limit saturation",
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+ "max_joint_limit_excess_rad": "diagnostic maximum operating/soft-limit excess observed in radians; hard-limit source and role validation are in robot_constraint_diagnostics",
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+ "safety_violation_rate_time": "compatibility diagnostic; with fixed physics_dt this is equivalent to safety_violation_step_rate and is omitted from grouped summary output",
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+ "safety_violation_step_rate": "core safety metric: fraction of executed steps with task-level safety violations; joint-limit observations are excluded by default",
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+ "safety_violation_rate_event": "deprecated compatibility alias of safety_violation_events_per_step; omitted from grouped summary output",
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+ "safety_violation_events_per_step": "diagnostic event density; may exceed 1 when multiple violations happen in one step",
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+ "episode_violation_rate": "compatibility alias of hard_violation_rate; omitted from grouped core output",
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+ "latched_stage_completion_rate": "main progress metric; ever-reached stage completion rate at episode end",
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+ "current_stage_completion_rate": "diagnostic terminal-state stage completion rate at episode end",
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+ "current_normalized_progress_score": "chain-depth diagnostic; normalized progress score at episode end",
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+ "current_chain_depth_progress_score": "alias of current_normalized_progress_score for ordered dependency-depth diagnostics",
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+ "latched_chain_depth_progress_score": "alias of latched_normalized_progress_score for ever-reached dependency-depth diagnostics",
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+ "robustness": "success rates grouped by benchmark protocol category: cov, inv, and inv+cov"
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+ }
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+ "high_speed_obj_058_golf_ball_4": 3,
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+ "runtime.soft_joint_pos_limits": 10
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+ "unknown_runtime_joint_names": [],
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+ "baseline_checks": {
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+ "per_object_best_kinematic_grasp_stability": {
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+ "obj_053_mini_soccer_ball_2": 0.8429700090279171,
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+ "obj_056_tennis_ball_3": 0.7501144634352336,
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+ "obj_058_golf_ball_4": 0.6582300475117814,
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+ "obj_144_table_tennis_5": 0.5581942281640864
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+ "mean_duration_score": 0.46322743964187374,
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+ "mean_hold_score": 0.33652721456083634,
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+ "mean_legacy_gsi": 0.41907977307571204,
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gpt6_astra_1x_icl/per_task_eval/32_baking_tray_prep_with_tools/Full/per_episode.jsonl ADDED
The diff for this file is too large to render. See raw diff
 
gpt6_astra_1x_icl/per_task_eval/32_baking_tray_prep_with_tools/Full/summary.json ADDED
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+ {
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+ "metadata": {
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+ "task_efficiency": "benchmark-specific expert-normalized speed ratio: expert_time_s / time_to_stable_success_s over reached-success episodes",
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+ "avg_steps_to_success": "diagnostic mean steps_to_stable_success over reached-success episodes, or None if no episode succeeds",
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+ "avg_policy_steps_to_success": "diagnostic mean policy-rate control/action steps through stable success over reached-success episodes",
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+ "avg_policy_queries_to_success": "diagnostic mean actual model inference queries through stable success over reached-success episodes; None when the first-success query count was not observed",
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+ "safe_success_rate": "episode success rate with no task-level hard safety violation (drop or tracked-object high speed; joint limits are diagnostic by default)",
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+ "hard_violation_rate": "episode rate with any task-level hard safety violation (drop or tracked-object high speed; joint limits are diagnostic by default)",
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+ "drop_rate": "episode rate with drop_off_table or drop_to_table_after_lift violation",
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+ "high_speed_violation_rate": "episode rate with any tracked object exceeding the configured speed threshold",
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+ "excessive_impact_rate": "deprecated contact-force impact metric; no longer populated by core safety",
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+ "robot_constraint_violation_rate": "diagnostic episode rate with any asset hard-joint-limit observation; excluded from safe_success_rate unless include_in_core_safety is explicitly enabled",
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+ "finger_joint_limit_saturation_rate": "episode rate with dexterous finger joints saturated beyond finger joint-limit thresholds; diagnostic by default and not included in safe_success_rate",
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+ "joint_limit_active_step_rate": "diagnostic mean fraction of steps with any joint exceeding the soft diagnostic margin",
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+ "finger_joint_limit_saturation_step_rate": "diagnostic mean fraction of steps with finger joint-limit saturation",
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+ "max_joint_limit_excess_rad": "diagnostic maximum operating/soft-limit excess observed in radians; hard-limit source and role validation are in robot_constraint_diagnostics",
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+ "safety_violation_rate_time": "compatibility diagnostic; with fixed physics_dt this is equivalent to safety_violation_step_rate and is omitted from grouped summary output",
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+ "safety_violation_step_rate": "core safety metric: fraction of executed steps with task-level safety violations; joint-limit observations are excluded by default",
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+ "safety_violation_rate_event": "deprecated compatibility alias of safety_violation_events_per_step; omitted from grouped summary output",
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+ "safety_violation_events_per_step": "diagnostic event density; may exceed 1 when multiple violations happen in one step",
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+ "episode_violation_rate": "compatibility alias of hard_violation_rate; omitted from grouped core output",
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+ "latched_stage_completion_rate": "main progress metric; ever-reached stage completion rate at episode end",
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+ "current_stage_completion_rate": "diagnostic terminal-state stage completion rate at episode end",
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+ "current_normalized_progress_score": "chain-depth diagnostic; normalized progress score at episode end",
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+ "current_chain_depth_progress_score": "alias of current_normalized_progress_score for ordered dependency-depth diagnostics",
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+ "latched_chain_depth_progress_score": "alias of latched_normalized_progress_score for ever-reached dependency-depth diagnostics",
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+ "robustness": "success rates grouped by benchmark protocol category: cov, inv, and inv+cov"
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+ "avg_current_chain_depth": 0.2,
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+ "drop_to_table_obj_009_gelatin_box_3": 1,
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+ "drop_to_table_obj_033_spatula_4": 1,
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+ "finger_joint_limit_saturation_step_rate": 0.037363067292644755,
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+ "max_joint_limit_excess_rad": 2.900862455368042,
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+ "joint_limit_hard_counts": {
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+ "left_middle_DIP": 8,
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+ "left_ring_DIP": 4,
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171
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173
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+ "joint_limit_hard_episode_events": 70,
176
+ "finger_joint_limit_saturation_counts": {
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+ "left_middle_DIP": 64,
178
+ "left_middle_PIP": 23,
179
+ "left_pinky_CMC": 242,
180
+ "left_pinky_DIP": 68,
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+ "left_ring_DIP": 33,
182
+ "left_thumb_CMC_AA": 13,
183
+ "left_thumb_MCP_AA": 3,
184
+ "multi_right_index_DIP": 61,
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+ "multi_right_index_MCP_FE": 80,
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+ "multi_right_middle_PIP": 94,
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201
+ "multi_right_thumb_MCP_FE": 50
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+ "A2": 9.959936141967773e-05,
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+ "left_ring_MCP_AA": 0.0045351386070251465,
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+ "left_ring_PIP": 0.057178858667612076,
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+ "left_thumb_CMC_AA": 0.14517754316329956,
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+ "left_thumb_CMC_FE": 0.0029706209897994995,
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+ "left_thumb_IP": 0.00015700132644269615,
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+ "left_thumb_MCP_AA": 0.26343855261802673,
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+ "multi_right_index_DIP": 1.5347728729248047,
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+ "multi_right_middle_MCP_FE": 0.1781976819038391,
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+ "multi_right_middle_PIP": 0.9427446126937866,
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+ "coverage": {
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+ "unavailable": 0,
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+ "unknown": 0
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+ },
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+ "joint_role_manifest": {
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+ "available": 10,
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+ "unavailable": 0,
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+ "unknown": 0
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+ }
257
+ },
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+ "hard_limit_sources": {
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+ "runtime.joint_pos_limits": 10
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+ },
261
+ "soft_limit_sources": {
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+ "runtime.soft_joint_pos_limits": 10
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+ },
264
+ "unknown_runtime_joint_names": [],
265
+ "baseline_checks": {
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+ "post_home": {
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+ "checked": 10,
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+ "hard_violation_episodes": 0
269
+ },
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+ "post_reset": {
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+ "checked": 10,
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+ "hard_violation_episodes": 0
273
+ }
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+ }
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+ }
276
+ },
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+ "robot_motion": {
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+ "joint_acceleration_rms": 41.85202679742137,
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+ "joint_effort_rms": 43.6663283644778,
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+ "joint_jerk_rms": 4176.809250717952,
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+ "joint_velocity_rms": 0.7754996672267569
282
+ },
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+ "grasp": {
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+ "kinematic_grasp_stability_index": 0.6549562059102851,
285
+ "mean_kinematic_grasp_stability": 0.3007984859248549,
286
+ "per_object_best_kinematic_grasp_stability": {
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+ "obj_008_pudding_box_2": 0.0,
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+ "obj_009_gelatin_box_3": 0.3662892199049133,
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+ "obj_033_spatula_4": 0.3254284429457169,
290
+ "obj_189_brush_5": 0.39449756256106144
291
+ },
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+ "grasp_gsi_diagnostics": {
293
+ "mean_anti_slip_score": 0.9704225352112645,
294
+ "mean_duration_score": 0.06400723787167452,
295
+ "mean_hold_score": 0.04528022300469473,
296
+ "mean_kinematic_stability_score": 0.02021204991771197,
297
+ "mean_legacy_gsi": 0.23476010926168536,
298
+ "mean_lift_score": 0.0626858372456964,
299
+ "mean_motion_stability_score": 0.04377626796963671
300
+ }
301
+ },
302
+ "tool": {
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+ "tool_selection_accuracy": null,
304
+ "tool_switch_success_rate": null,
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+ "tool_switch_total": 0,
306
+ "tool_switch_successful": 0
307
+ },
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+ "runtime": {
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+ "avg_steps": 2556,
310
+ "error_count": 0
311
+ }
312
+ }
313
+ }
gpt6_astra_1x_icl/per_task_eval/34_fridge_wine_interhand_pour/Full/per_episode.jsonl ADDED
The diff for this file is too large to render. See raw diff
 
gpt6_astra_1x_icl/per_task_eval/34_fridge_wine_interhand_pour/Full/summary.json ADDED
@@ -0,0 +1,315 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "metric_schema_version": "core-v1.8-policy-step-query-split",
3
+ "metadata": {
4
+ "policy_name": "gpt-6-astra",
5
+ "base_seed": 203400000,
6
+ "seed_policy": "episode_seed = base_seed + episode_index - 1",
7
+ "randomization_recorded": true,
8
+ "n_episodes": 10,
9
+ "successes": 3,
10
+ "error_count": 0,
11
+ "evaluation_protocol": "reach_and_stop",
12
+ "early_stop": true,
13
+ "success_definition": "terminal.raw_condition holds for dwell_time_s",
14
+ "measurement_window": "episode_start_to_stable_success_or_failure_budget",
15
+ "max_episode_steps": 3240,
16
+ "dwell_time_s": 0.5,
17
+ "field_semantics": {
18
+ "success_rate": "primary protocol success rate: stable_success for reach_and_stop; terminal at_end_success_budget for fixed_horizon",
19
+ "avg_time_to_success_s": "main efficiency metric: mean time_to_stable_success_s over reached-success episodes",
20
+ "task_efficiency": "benchmark-specific expert-normalized speed ratio: expert_time_s / time_to_stable_success_s over reached-success episodes",
21
+ "avg_steps_to_success": "diagnostic mean steps_to_stable_success over reached-success episodes, or None if no episode succeeds",
22
+ "avg_policy_steps_to_success": "diagnostic mean policy-rate control/action steps through stable success over reached-success episodes",
23
+ "avg_policy_queries_to_success": "diagnostic mean actual model inference queries through stable success over reached-success episodes; None when the first-success query count was not observed",
24
+ "safe_success_rate": "episode success rate with no task-level hard safety violation (drop or tracked-object high speed; joint limits are diagnostic by default)",
25
+ "hard_violation_rate": "episode rate with any task-level hard safety violation (drop or tracked-object high speed; joint limits are diagnostic by default)",
26
+ "drop_rate": "episode rate with drop_off_table or drop_to_table_after_lift violation",
27
+ "high_speed_violation_rate": "episode rate with any tracked object exceeding the configured speed threshold",
28
+ "excessive_impact_rate": "deprecated contact-force impact metric; no longer populated by core safety",
29
+ "robot_constraint_violation_rate": "diagnostic episode rate with any asset hard-joint-limit observation; excluded from safe_success_rate unless include_in_core_safety is explicitly enabled",
30
+ "finger_joint_limit_saturation_rate": "episode rate with dexterous finger joints saturated beyond finger joint-limit thresholds; diagnostic by default and not included in safe_success_rate",
31
+ "joint_limit_active_step_rate": "diagnostic mean fraction of steps with any joint exceeding the soft diagnostic margin",
32
+ "finger_joint_limit_saturation_step_rate": "diagnostic mean fraction of steps with finger joint-limit saturation",
33
+ "max_joint_limit_excess_rad": "diagnostic maximum operating/soft-limit excess observed in radians; hard-limit source and role validation are in robot_constraint_diagnostics",
34
+ "safety_violation_rate_time": "compatibility diagnostic; with fixed physics_dt this is equivalent to safety_violation_step_rate and is omitted from grouped summary output",
35
+ "safety_violation_step_rate": "core safety metric: fraction of executed steps with task-level safety violations; joint-limit observations are excluded by default",
36
+ "safety_violation_rate_event": "deprecated compatibility alias of safety_violation_events_per_step; omitted from grouped summary output",
37
+ "safety_violation_events_per_step": "diagnostic event density; may exceed 1 when multiple violations happen in one step",
38
+ "episode_violation_rate": "compatibility alias of hard_violation_rate; omitted from grouped core output",
39
+ "latched_stage_completion_rate": "main progress metric; ever-reached stage completion rate at episode end",
40
+ "current_stage_completion_rate": "diagnostic terminal-state stage completion rate at episode end",
41
+ "current_normalized_progress_score": "chain-depth diagnostic; normalized progress score at episode end",
42
+ "current_chain_depth_progress_score": "alias of current_normalized_progress_score for ordered dependency-depth diagnostics",
43
+ "latched_chain_depth_progress_score": "alias of latched_normalized_progress_score for ever-reached dependency-depth diagnostics",
44
+ "robustness": "success rates grouped by benchmark protocol category: cov, inv, and inv+cov"
45
+ }
46
+ },
47
+ "core_metrics": {
48
+ "completion": {
49
+ "success_rate": 0.3,
50
+ "success_rate_ci": {
51
+ "mean": 0.3,
52
+ "ci_low": 0.0,
53
+ "ci_high": 0.6
54
+ }
55
+ },
56
+ "progress": {
57
+ "latched_stage_completion_rate": 0.6799999999999999
58
+ },
59
+ "efficiency": {
60
+ "avg_time_to_success_s": 47.79999999999857
61
+ },
62
+ "safety": {
63
+ "safe_success_rate": 0.2,
64
+ "hard_violation_rate": 0.7,
65
+ "drop_rate": 0.7,
66
+ "high_speed_violation_rate": 0.0,
67
+ "safety_violation_step_rate": 0.00022375655287047692
68
+ },
69
+ "robustness": {}
70
+ },
71
+ "diagnostic_metrics": {
72
+ "completion": {
73
+ "ever_instant_success_rate": 0.3,
74
+ "at_end_success_rate": 0.3,
75
+ "task_family_success_rate": {
76
+ "articulation_pour": 0.3
77
+ }
78
+ },
79
+ "progress": {
80
+ "current_stage_completion_rate": 0.42,
81
+ "current_chain_depth_progress_score": 0.62,
82
+ "latched_chain_depth_progress_score": 0.6799999999999999,
83
+ "avg_current_chain_depth": 3.1,
84
+ "avg_latched_chain_depth": 3.4
85
+ },
86
+ "efficiency": {
87
+ "task_efficiency": 0.7564199283806476,
88
+ "expert_time_s": 36.0,
89
+ "expert_time_step": 2160,
90
+ "avg_steps_to_success": 2868,
91
+ "avg_policy_steps_to_success": 956.3333333333334,
92
+ "avg_policy_queries_to_success": 27.666666666666668
93
+ },
94
+ "safety": {
95
+ "safety_violation_events_per_step": 0.00022375655287047692,
96
+ "violation_counts": {
97
+ "drop_to_table_obj_224_wine_bottle_1": 7
98
+ },
99
+ "robot_constraint_violation_rate": 1.0,
100
+ "finger_joint_limit_saturation_rate": 1.0,
101
+ "joint_limit_active_step_rate": 0.3917018284106892,
102
+ "finger_joint_limit_saturation_step_rate": 0.3418360823424115,
103
+ "max_joint_limit_excess_rad": 2.037945032119751,
104
+ "robot_constraint_diagnostics": {
105
+ "joint_limit_soft_counts": {
106
+ "left_index_dip_joint": 61,
107
+ "left_index_mcp_joint": 12,
108
+ "left_index_pip_joint": 697,
109
+ "left_index_pitch_joint": 494,
110
+ "left_middle_dip_joint": 40,
111
+ "left_middle_mcp_joint": 61,
112
+ "left_middle_pip_joint": 1173,
113
+ "left_middle_pitch_joint": 344,
114
+ "left_pinky_mcp_joint": 213,
115
+ "left_pinky_pip_joint": 140,
116
+ "left_ring_dip_joint": 27,
117
+ "left_ring_mcp_joint": 277,
118
+ "left_ring_pip_joint": 896,
119
+ "left_thumb_dip_joint": 56,
120
+ "left_thumb_mcp_joint": 3259,
121
+ "left_thumb_pip_joint": 125,
122
+ "left_thumb_yaw_joint": 32,
123
+ "right_index_dip_joint": 272,
124
+ "right_index_mcp_joint": 251,
125
+ "right_index_pip_joint": 645,
126
+ "right_index_pitch_joint": 379,
127
+ "right_middle_dip_joint": 327,
128
+ "right_middle_mcp_joint": 436,
129
+ "right_middle_pip_joint": 634,
130
+ "right_middle_pitch_joint": 300,
131
+ "right_pinky_dip_joint": 6,
132
+ "right_pinky_mcp_joint": 378,
133
+ "right_pinky_pip_joint": 356,
134
+ "right_ring_dip_joint": 393,
135
+ "right_ring_mcp_joint": 383,
136
+ "right_ring_pip_joint": 732,
137
+ "right_thumb_dip_joint": 141,
138
+ "right_thumb_mcp_joint": 6681,
139
+ "right_thumb_pip_joint": 94,
140
+ "right_thumb_yaw_joint": 92
141
+ },
142
+ "joint_limit_hard_counts": {
143
+ "left_index_dip_joint": 4,
144
+ "left_index_mcp_joint": 2,
145
+ "left_index_pip_joint": 89,
146
+ "left_index_pitch_joint": 17,
147
+ "left_middle_dip_joint": 3,
148
+ "left_middle_mcp_joint": 5,
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+ "left_middle_pip_joint": 62,
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+ "left_middle_pitch_joint": 14,
151
+ "left_pinky_mcp_joint": 22,
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+ "left_pinky_pip_joint": 10,
153
+ "left_ring_dip_joint": 4,
154
+ "left_ring_mcp_joint": 24,
155
+ "left_ring_pip_joint": 57,
156
+ "left_thumb_dip_joint": 1,
157
+ "left_thumb_mcp_joint": 37,
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+ "left_thumb_pip_joint": 4,
159
+ "left_thumb_yaw_joint": 2,
160
+ "right_index_dip_joint": 16,
161
+ "right_index_mcp_joint": 2,
162
+ "right_index_pip_joint": 8,
163
+ "right_index_pitch_joint": 12,
164
+ "right_middle_dip_joint": 24,
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+ "right_middle_mcp_joint": 4,
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+ "right_middle_pip_joint": 8,
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+ "right_middle_pitch_joint": 8,
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+ "right_pinky_dip_joint": 1,
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+ "right_pinky_mcp_joint": 15,
170
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+ "right_ring_dip_joint": 15,
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+ "right_ring_pip_joint": 6,
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+ "right_thumb_dip_joint": 8,
175
+ "right_thumb_mcp_joint": 15,
176
+ "right_thumb_pip_joint": 2,
177
+ "right_thumb_yaw_joint": 2
178
+ },
179
+ "joint_limit_hard_episode_events": 167,
180
+ "finger_joint_limit_saturation_counts": {
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+ "left_index_dip_joint": 35,
182
+ "left_index_pip_joint": 348,
183
+ "left_index_pitch_joint": 336,
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+ "left_middle_dip_joint": 7,
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+ "left_ring_mcp_joint": 171,
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+ "left_thumb_mcp_joint": 2601,
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+ "right_index_dip_joint": 141,
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199
+ "right_middle_dip_joint": 191,
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+ "right_middle_pitch_joint": 218,
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+ "right_pinky_mcp_joint": 253,
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211
+ "right_thumb_yaw_joint": 68
212
+ },
213
+ "joint_limit_max_excess_by_joint": {
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+ "left_index_dip_joint": 0.2799852788448334,
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222
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223
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+ "left_ring_pip_joint": 1.2001138925552368,
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+ "right_index_pitch_joint": 0.7631471753120422,
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+ "right_middle_mcp_joint": 0.5970035791397095,
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+ "right_middle_pip_joint": 1.8758935928344727,
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+ "right_middle_pitch_joint": 0.835150420665741,
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+ "right_pinky_dip_joint": 0.22969281673431396,
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+ "right_pinky_mcp_joint": 0.9765199422836304,
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+ "right_pinky_pip_joint": 1.4550007581710815,
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+ "right_ring_dip_joint": 1.306758165359497,
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+ "right_ring_mcp_joint": 0.5623847246170044,
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+ }
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+ }
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+ }
gpt6_astra_1x_icl/per_task_eval/42_trash_disposal/Full/per_episode.jsonl ADDED
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gpt6_astra_1x_icl/per_task_eval/42_trash_disposal/Full/summary.json ADDED
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1
+ {
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+ "metadata": {
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+ "policy_name": "gpt-6-astra",
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+ "base_seed": 204200000,
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+ "seed_policy": "episode_seed = base_seed + episode_index - 1",
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+ "max_episode_steps": 2004,
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+ "dwell_time_s": 0.5,
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+ "field_semantics": {
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+ "success_rate": "primary protocol success rate: stable_success for reach_and_stop; terminal at_end_success_budget for fixed_horizon",
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+ "avg_time_to_success_s": "main efficiency metric: mean time_to_stable_success_s over reached-success episodes",
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+ "task_efficiency": "benchmark-specific expert-normalized speed ratio: expert_time_s / time_to_stable_success_s over reached-success episodes",
21
+ "avg_steps_to_success": "diagnostic mean steps_to_stable_success over reached-success episodes, or None if no episode succeeds",
22
+ "avg_policy_steps_to_success": "diagnostic mean policy-rate control/action steps through stable success over reached-success episodes",
23
+ "avg_policy_queries_to_success": "diagnostic mean actual model inference queries through stable success over reached-success episodes; None when the first-success query count was not observed",
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+ "safe_success_rate": "episode success rate with no task-level hard safety violation (drop or tracked-object high speed; joint limits are diagnostic by default)",
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+ "hard_violation_rate": "episode rate with any task-level hard safety violation (drop or tracked-object high speed; joint limits are diagnostic by default)",
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+ "drop_rate": "episode rate with drop_off_table or drop_to_table_after_lift violation",
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+ "high_speed_violation_rate": "episode rate with any tracked object exceeding the configured speed threshold",
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+ "excessive_impact_rate": "deprecated contact-force impact metric; no longer populated by core safety",
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+ "robot_constraint_violation_rate": "diagnostic episode rate with any asset hard-joint-limit observation; excluded from safe_success_rate unless include_in_core_safety is explicitly enabled",
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+ "finger_joint_limit_saturation_rate": "episode rate with dexterous finger joints saturated beyond finger joint-limit thresholds; diagnostic by default and not included in safe_success_rate",
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+ "joint_limit_active_step_rate": "diagnostic mean fraction of steps with any joint exceeding the soft diagnostic margin",
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+ "safety_violation_rate_time": "compatibility diagnostic; with fixed physics_dt this is equivalent to safety_violation_step_rate and is omitted from grouped summary output",
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+ "safety_violation_step_rate": "core safety metric: fraction of executed steps with task-level safety violations; joint-limit observations are excluded by default",
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+ "safety_violation_rate_event": "deprecated compatibility alias of safety_violation_events_per_step; omitted from grouped summary output",
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+ "safety_violation_events_per_step": "diagnostic event density; may exceed 1 when multiple violations happen in one step",
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+ "episode_violation_rate": "compatibility alias of hard_violation_rate; omitted from grouped core output",
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+ "latched_stage_completion_rate": "main progress metric; ever-reached stage completion rate at episode end",
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+ "current_stage_completion_rate": "diagnostic terminal-state stage completion rate at episode end",
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+ "current_normalized_progress_score": "chain-depth diagnostic; normalized progress score at episode end",
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+ "current_chain_depth_progress_score": "alias of current_normalized_progress_score for ordered dependency-depth diagnostics",
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+ "latched_chain_depth_progress_score": "alias of latched_normalized_progress_score for ever-reached dependency-depth diagnostics",
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+ "robustness": "success rates grouped by benchmark protocol category: cov, inv, and inv+cov"
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+ }
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+ },
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+ "core_metrics": {
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+ "completion": {
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+ "hard_violation_rate": 0.9,
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+ "high_speed_violation_rate": 0.8,
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+ "task_family_success_rate": {
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+ "avg_current_chain_depth": 2.1,
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+ "avg_latched_chain_depth": 2.1
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+ "violation_counts": {
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+ "drop_obj_080_bottle_3": 5,
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+ "drop_to_table_obj_080_bottle_3": 1,
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+ "drop_to_table_obj_341_banana_peel_1": 7,
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+ "drop_to_table_obj_349_paper_low_2": 4,
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+ "high_speed_obj_080_bottle_3": 2,
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+ "high_speed_obj_341_banana_peel_1": 2,
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+ "high_speed_obj_349_paper_low_2": 10
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+ "joint_limit_max_excess_by_joint": {
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+ "baseline_checks": {
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+ "per_object_best_kinematic_grasp_stability": {
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+ "obj_080_bottle_3": 0.5705879291621311,
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gpt6_astra_1x_icl/per_task_eval/43_fridge_fruit_shelf_sorting/Full/per_episode.jsonl ADDED
The diff for this file is too large to render. See raw diff
 
gpt6_astra_1x_icl/per_task_eval/43_fridge_fruit_shelf_sorting/Full/summary.json ADDED
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1
+ {
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+ "metadata": {
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+ "policy_name": "gpt-6-astra",
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+ "base_seed": 204300000,
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+ "seed_policy": "episode_seed = base_seed + episode_index - 1",
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+ "randomization_recorded": true,
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+ "evaluation_protocol": "reach_and_stop",
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+ "early_stop": true,
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+ "success_definition": "terminal.raw_condition holds for dwell_time_s",
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+ "measurement_window": "episode_start_to_stable_success_or_failure_budget",
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+ "max_episode_steps": 4125,
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+ "dwell_time_s": 0.5,
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+ "field_semantics": {
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+ "success_rate": "primary protocol success rate: stable_success for reach_and_stop; terminal at_end_success_budget for fixed_horizon",
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+ "avg_time_to_success_s": "main efficiency metric: mean time_to_stable_success_s over reached-success episodes",
20
+ "task_efficiency": "benchmark-specific expert-normalized speed ratio: expert_time_s / time_to_stable_success_s over reached-success episodes",
21
+ "avg_steps_to_success": "diagnostic mean steps_to_stable_success over reached-success episodes, or None if no episode succeeds",
22
+ "avg_policy_steps_to_success": "diagnostic mean policy-rate control/action steps through stable success over reached-success episodes",
23
+ "avg_policy_queries_to_success": "diagnostic mean actual model inference queries through stable success over reached-success episodes; None when the first-success query count was not observed",
24
+ "safe_success_rate": "episode success rate with no task-level hard safety violation (drop or tracked-object high speed; joint limits are diagnostic by default)",
25
+ "hard_violation_rate": "episode rate with any task-level hard safety violation (drop or tracked-object high speed; joint limits are diagnostic by default)",
26
+ "drop_rate": "episode rate with drop_off_table or drop_to_table_after_lift violation",
27
+ "high_speed_violation_rate": "episode rate with any tracked object exceeding the configured speed threshold",
28
+ "excessive_impact_rate": "deprecated contact-force impact metric; no longer populated by core safety",
29
+ "robot_constraint_violation_rate": "diagnostic episode rate with any asset hard-joint-limit observation; excluded from safe_success_rate unless include_in_core_safety is explicitly enabled",
30
+ "finger_joint_limit_saturation_rate": "episode rate with dexterous finger joints saturated beyond finger joint-limit thresholds; diagnostic by default and not included in safe_success_rate",
31
+ "joint_limit_active_step_rate": "diagnostic mean fraction of steps with any joint exceeding the soft diagnostic margin",
32
+ "finger_joint_limit_saturation_step_rate": "diagnostic mean fraction of steps with finger joint-limit saturation",
33
+ "max_joint_limit_excess_rad": "diagnostic maximum operating/soft-limit excess observed in radians; hard-limit source and role validation are in robot_constraint_diagnostics",
34
+ "safety_violation_rate_time": "compatibility diagnostic; with fixed physics_dt this is equivalent to safety_violation_step_rate and is omitted from grouped summary output",
35
+ "safety_violation_step_rate": "core safety metric: fraction of executed steps with task-level safety violations; joint-limit observations are excluded by default",
36
+ "safety_violation_rate_event": "deprecated compatibility alias of safety_violation_events_per_step; omitted from grouped summary output",
37
+ "safety_violation_events_per_step": "diagnostic event density; may exceed 1 when multiple violations happen in one step",
38
+ "episode_violation_rate": "compatibility alias of hard_violation_rate; omitted from grouped core output",
39
+ "latched_stage_completion_rate": "main progress metric; ever-reached stage completion rate at episode end",
40
+ "current_stage_completion_rate": "diagnostic terminal-state stage completion rate at episode end",
41
+ "current_normalized_progress_score": "chain-depth diagnostic; normalized progress score at episode end",
42
+ "current_chain_depth_progress_score": "alias of current_normalized_progress_score for ordered dependency-depth diagnostics",
43
+ "latched_chain_depth_progress_score": "alias of latched_normalized_progress_score for ever-reached dependency-depth diagnostics",
44
+ "robustness": "success rates grouped by benchmark protocol category: cov, inv, and inv+cov"
45
+ }
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+ },
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+ "core_metrics": {
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+ "completion": {
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+ "success_rate": 0.3,
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+ }
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+ },
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+ "safety_violation_step_rate": 0.0013635194237200925
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+ "task_family_success_rate": {
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+ }
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+ "avg_current_chain_depth": 1.6,
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+ "avg_latched_chain_depth": 1.9
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+ },
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+ },
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+ "drop_to_table_obj_013_apple_1": 6,
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+ "high_speed_obj_013_apple_1": 13
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+ },
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+ },
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+ "available": 10,
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+ },
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+ "joint_role_manifest": {
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+ }
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+ },
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+ "hard_limit_sources": {
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+ "runtime.joint_pos_limits": 10
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+ },
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+ "soft_limit_sources": {
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+ "runtime.soft_joint_pos_limits": 10
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+ },
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+ "unknown_runtime_joint_names": [],
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+ "baseline_checks": {
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+ "post_home": {
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+ },
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+ "post_reset": {
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+ "hard_violation_episodes": 0
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+ }
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+ }
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+ }
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+ },
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+ "robot_motion": {
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+ "joint_acceleration_rms": 21.6003658770578,
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+ "joint_effort_rms": 52.903143749283146,
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+ "joint_jerk_rms": 2143.0483888617514,
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+ "joint_velocity_rms": 0.5002505032033382
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+ },
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+ "grasp": {
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+ "kinematic_grasp_stability_index": 0.9489701401741613,
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+ "mean_kinematic_grasp_stability": 0.4333703160657618,
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+ "per_object_best_kinematic_grasp_stability": {
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+ "obj_011_banana_2": 0.8037451133980107,
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+ "obj_013_apple_1": 0.9116650967013875
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+ },
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+ "grasp_gsi_diagnostics": {
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+ "mean_anti_slip_score": 0.7634205380824515,
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+ "mean_duration_score": 0.6876188743290731,
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+ "mean_hold_score": 0.31131175593053584,
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+ "mean_kinematic_stability_score": 0.16574074223314023,
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+ "mean_legacy_gsi": 0.47877921251336375,
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+ "mean_lift_score": 0.402605518136838,
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+ "mean_motion_stability_score": 0.3023697254228749
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+ }
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+ },
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+ "tool": {
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+ "tool_switch_success_rate": null,
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+ "tool_switch_total": 0,
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+ },
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+ "runtime": {
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338
+ "error_count": 1
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+ }
340
+ }
341
+ }
gpt6_astra_1x_icl/per_task_eval/44_microwave_bowl_loading/Full/per_episode.jsonl ADDED
The diff for this file is too large to render. See raw diff
 
gpt6_astra_1x_icl/per_task_eval/44_microwave_bowl_loading/Full/summary.json ADDED
@@ -0,0 +1,294 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "metric_schema_version": "core-v1.8-policy-step-query-split",
3
+ "metadata": {
4
+ "policy_name": "gpt-6-astra",
5
+ "base_seed": 204400000,
6
+ "seed_policy": "episode_seed = base_seed + episode_index - 1",
7
+ "randomization_recorded": true,
8
+ "n_episodes": 10,
9
+ "successes": 4,
10
+ "error_count": 0,
11
+ "evaluation_protocol": "reach_and_stop",
12
+ "early_stop": true,
13
+ "success_definition": "terminal.raw_condition holds for dwell_time_s",
14
+ "measurement_window": "episode_start_to_stable_success_or_failure_budget",
15
+ "max_episode_steps": 3183,
16
+ "dwell_time_s": 0.5,
17
+ "field_semantics": {
18
+ "success_rate": "primary protocol success rate: stable_success for reach_and_stop; terminal at_end_success_budget for fixed_horizon",
19
+ "avg_time_to_success_s": "main efficiency metric: mean time_to_stable_success_s over reached-success episodes",
20
+ "task_efficiency": "benchmark-specific expert-normalized speed ratio: expert_time_s / time_to_stable_success_s over reached-success episodes",
21
+ "avg_steps_to_success": "diagnostic mean steps_to_stable_success over reached-success episodes, or None if no episode succeeds",
22
+ "avg_policy_steps_to_success": "diagnostic mean policy-rate control/action steps through stable success over reached-success episodes",
23
+ "avg_policy_queries_to_success": "diagnostic mean actual model inference queries through stable success over reached-success episodes; None when the first-success query count was not observed",
24
+ "safe_success_rate": "episode success rate with no task-level hard safety violation (drop or tracked-object high speed; joint limits are diagnostic by default)",
25
+ "hard_violation_rate": "episode rate with any task-level hard safety violation (drop or tracked-object high speed; joint limits are diagnostic by default)",
26
+ "drop_rate": "episode rate with drop_off_table or drop_to_table_after_lift violation",
27
+ "high_speed_violation_rate": "episode rate with any tracked object exceeding the configured speed threshold",
28
+ "excessive_impact_rate": "deprecated contact-force impact metric; no longer populated by core safety",
29
+ "robot_constraint_violation_rate": "diagnostic episode rate with any asset hard-joint-limit observation; excluded from safe_success_rate unless include_in_core_safety is explicitly enabled",
30
+ "finger_joint_limit_saturation_rate": "episode rate with dexterous finger joints saturated beyond finger joint-limit thresholds; diagnostic by default and not included in safe_success_rate",
31
+ "joint_limit_active_step_rate": "diagnostic mean fraction of steps with any joint exceeding the soft diagnostic margin",
32
+ "finger_joint_limit_saturation_step_rate": "diagnostic mean fraction of steps with finger joint-limit saturation",
33
+ "max_joint_limit_excess_rad": "diagnostic maximum operating/soft-limit excess observed in radians; hard-limit source and role validation are in robot_constraint_diagnostics",
34
+ "safety_violation_rate_time": "compatibility diagnostic; with fixed physics_dt this is equivalent to safety_violation_step_rate and is omitted from grouped summary output",
35
+ "safety_violation_step_rate": "core safety metric: fraction of executed steps with task-level safety violations; joint-limit observations are excluded by default",
36
+ "safety_violation_rate_event": "deprecated compatibility alias of safety_violation_events_per_step; omitted from grouped summary output",
37
+ "safety_violation_events_per_step": "diagnostic event density; may exceed 1 when multiple violations happen in one step",
38
+ "episode_violation_rate": "compatibility alias of hard_violation_rate; omitted from grouped core output",
39
+ "latched_stage_completion_rate": "main progress metric; ever-reached stage completion rate at episode end",
40
+ "current_stage_completion_rate": "diagnostic terminal-state stage completion rate at episode end",
41
+ "current_normalized_progress_score": "chain-depth diagnostic; normalized progress score at episode end",
42
+ "current_chain_depth_progress_score": "alias of current_normalized_progress_score for ordered dependency-depth diagnostics",
43
+ "latched_chain_depth_progress_score": "alias of latched_normalized_progress_score for ever-reached dependency-depth diagnostics",
44
+ "robustness": "success rates grouped by benchmark protocol category: cov, inv, and inv+cov"
45
+ }
46
+ },
47
+ "core_metrics": {
48
+ "completion": {
49
+ "success_rate": 0.4,
50
+ "success_rate_ci": {
51
+ "mean": 0.4,
52
+ "ci_low": 0.1,
53
+ "ci_high": 0.7
54
+ }
55
+ },
56
+ "progress": {
57
+ "latched_stage_completion_rate": 0.625
58
+ },
59
+ "efficiency": {
60
+ "avg_time_to_success_s": 42.0874999999989
61
+ },
62
+ "safety": {
63
+ "safe_success_rate": 0.4,
64
+ "hard_violation_rate": 0.6,
65
+ "drop_rate": 0.6,
66
+ "high_speed_violation_rate": 0.1,
67
+ "safety_violation_step_rate": 0.0004109729785266619
68
+ },
69
+ "robustness": {}
70
+ },
71
+ "diagnostic_metrics": {
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+ "completion": {
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+ "ever_instant_success_rate": 0.4,
74
+ "at_end_success_rate": 0.4,
75
+ "task_family_success_rate": {
76
+ "articulation_door_place": 0.4
77
+ }
78
+ },
79
+ "progress": {
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+ "current_stage_completion_rate": 0.425,
81
+ "current_chain_depth_progress_score": 0.525,
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+ "latched_chain_depth_progress_score": 0.625,
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+ "avg_current_chain_depth": 2.1,
84
+ "avg_latched_chain_depth": 2.5
85
+ },
86
+ "efficiency": {
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+ "expert_time_s": 35.36666666666667,
89
+ "expert_time_step": 2122,
90
+ "avg_steps_to_success": 2525.25,
91
+ "avg_policy_steps_to_success": 842.25,
92
+ "avg_policy_queries_to_success": 22.5
93
+ },
94
+ "safety": {
95
+ "safety_violation_events_per_step": 0.0003082297338949964,
96
+ "violation_counts": {
97
+ "drop_to_table_obj_024_bowl_3": 2,
98
+ "drop_to_table_obj_163_baguette_1": 6,
99
+ "high_speed_obj_163_baguette_1": 1
100
+ },
101
+ "robot_constraint_violation_rate": 1.0,
102
+ "finger_joint_limit_saturation_rate": 1.0,
103
+ "joint_limit_active_step_rate": 0.15298469125654987,
104
+ "finger_joint_limit_saturation_step_rate": 0.0633925819377376,
105
+ "max_joint_limit_excess_rad": 3.174018144607544,
106
+ "robot_constraint_diagnostics": {
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+ "joint_limit_soft_counts": {
108
+ "left_hand_Finger_Spread": 19,
109
+ "left_hand_Index_Finger_Distal": 61,
110
+ "left_hand_Index_Finger_Proximal": 475,
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+ "left_hand_Middle_Finger_Distal": 296,
112
+ "left_hand_Middle_Finger_Proximal": 933,
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+ "left_hand_Pinky": 132,
114
+ "left_hand_Ring_Finger": 1062,
115
+ "left_hand_Thumb_Flexion": 1116,
116
+ "left_hand_Thumb_Opposition": 1,
117
+ "left_hand_j12": 86,
118
+ "left_hand_j13": 184,
119
+ "left_hand_j3": 626,
120
+ "left_hand_j5": 568,
121
+ "left_hand_ring_spread": 17,
122
+ "right_hand_Index_Finger_Distal": 590,
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+ "right_hand_Index_Finger_Proximal": 12,
124
+ "right_hand_Middle_Finger_Distal": 23,
125
+ "right_hand_Middle_Finger_Proximal": 50,
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+ "right_hand_Pinky": 1,
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+ "right_hand_Ring_Finger": 2,
128
+ "right_hand_Thumb_Flexion": 281,
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+ "right_hand_index_spread": 9,
130
+ "right_hand_j12": 13,
131
+ "right_hand_j13": 3,
132
+ "right_hand_j3": 260,
133
+ "right_hand_j5": 1,
134
+ "right_hand_ring_spread": 10
135
+ },
136
+ "joint_limit_hard_counts": {
137
+ "left_hand_Finger_Spread": 41,
138
+ "left_hand_Index_Finger_Distal": 2,
139
+ "left_hand_Index_Finger_Proximal": 15,
140
+ "left_hand_Middle_Finger_Distal": 7,
141
+ "left_hand_Middle_Finger_Proximal": 29,
142
+ "left_hand_Pinky": 9,
143
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gpt6_astra_1x_icl/per_task_eval/51_toilet_lid_cleaner_pour/Full/per_episode.jsonl ADDED
The diff for this file is too large to render. See raw diff
 
gpt6_astra_1x_icl/per_task_eval/51_toilet_lid_cleaner_pour/Full/summary.json ADDED
@@ -0,0 +1,251 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "metric_schema_version": "core-v1.8-policy-step-query-split",
3
+ "metadata": {
4
+ "policy_name": "gpt-6-astra",
5
+ "base_seed": 205100000,
6
+ "seed_policy": "episode_seed = base_seed + episode_index - 1",
7
+ "randomization_recorded": true,
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+ "n_episodes": 10,
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+ "successes": 6,
10
+ "error_count": 1,
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+ "evaluation_protocol": "reach_and_stop",
12
+ "early_stop": true,
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+ "success_definition": "terminal.raw_condition holds for dwell_time_s",
14
+ "measurement_window": "episode_start_to_stable_success_or_failure_budget",
15
+ "max_episode_steps": 3069,
16
+ "dwell_time_s": 0.5,
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+ "field_semantics": {
18
+ "success_rate": "primary protocol success rate: stable_success for reach_and_stop; terminal at_end_success_budget for fixed_horizon",
19
+ "avg_time_to_success_s": "main efficiency metric: mean time_to_stable_success_s over reached-success episodes",
20
+ "task_efficiency": "benchmark-specific expert-normalized speed ratio: expert_time_s / time_to_stable_success_s over reached-success episodes",
21
+ "avg_steps_to_success": "diagnostic mean steps_to_stable_success over reached-success episodes, or None if no episode succeeds",
22
+ "avg_policy_steps_to_success": "diagnostic mean policy-rate control/action steps through stable success over reached-success episodes",
23
+ "avg_policy_queries_to_success": "diagnostic mean actual model inference queries through stable success over reached-success episodes; None when the first-success query count was not observed",
24
+ "safe_success_rate": "episode success rate with no task-level hard safety violation (drop or tracked-object high speed; joint limits are diagnostic by default)",
25
+ "hard_violation_rate": "episode rate with any task-level hard safety violation (drop or tracked-object high speed; joint limits are diagnostic by default)",
26
+ "drop_rate": "episode rate with drop_off_table or drop_to_table_after_lift violation",
27
+ "high_speed_violation_rate": "episode rate with any tracked object exceeding the configured speed threshold",
28
+ "excessive_impact_rate": "deprecated contact-force impact metric; no longer populated by core safety",
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+ "robot_constraint_violation_rate": "diagnostic episode rate with any asset hard-joint-limit observation; excluded from safe_success_rate unless include_in_core_safety is explicitly enabled",
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+ "finger_joint_limit_saturation_rate": "episode rate with dexterous finger joints saturated beyond finger joint-limit thresholds; diagnostic by default and not included in safe_success_rate",
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+ "joint_limit_active_step_rate": "diagnostic mean fraction of steps with any joint exceeding the soft diagnostic margin",
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+ "finger_joint_limit_saturation_step_rate": "diagnostic mean fraction of steps with finger joint-limit saturation",
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+ "max_joint_limit_excess_rad": "diagnostic maximum operating/soft-limit excess observed in radians; hard-limit source and role validation are in robot_constraint_diagnostics",
34
+ "safety_violation_rate_time": "compatibility diagnostic; with fixed physics_dt this is equivalent to safety_violation_step_rate and is omitted from grouped summary output",
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+ "safety_violation_step_rate": "core safety metric: fraction of executed steps with task-level safety violations; joint-limit observations are excluded by default",
36
+ "safety_violation_rate_event": "deprecated compatibility alias of safety_violation_events_per_step; omitted from grouped summary output",
37
+ "safety_violation_events_per_step": "diagnostic event density; may exceed 1 when multiple violations happen in one step",
38
+ "episode_violation_rate": "compatibility alias of hard_violation_rate; omitted from grouped core output",
39
+ "latched_stage_completion_rate": "main progress metric; ever-reached stage completion rate at episode end",
40
+ "current_stage_completion_rate": "diagnostic terminal-state stage completion rate at episode end",
41
+ "current_normalized_progress_score": "chain-depth diagnostic; normalized progress score at episode end",
42
+ "current_chain_depth_progress_score": "alias of current_normalized_progress_score for ordered dependency-depth diagnostics",
43
+ "latched_chain_depth_progress_score": "alias of latched_normalized_progress_score for ever-reached dependency-depth diagnostics",
44
+ "robustness": "success rates grouped by benchmark protocol category: cov, inv, and inv+cov"
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+ }
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+ },
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+ "completion": {
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+ "success_rate": 0.6,
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+ "hard_violation_rate": 0.3,
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+ "high_speed_violation_rate": 0.2,
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+ "drop_to_table_obj_021_bleach_cleanser_2": 2,
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+ "high_speed_obj_021_bleach_cleanser_2": 2
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gpt6_astra_1x_icl/per_task_eval/60_breadbasket_fast_food_loading/Full/per_episode.jsonl ADDED
The diff for this file is too large to render. See raw diff
 
gpt6_astra_1x_icl/per_task_eval/60_breadbasket_fast_food_loading/Full/summary.json ADDED
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1
+ {
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+ "metric_schema_version": "core-v1.8-policy-step-query-split",
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+ "metadata": {
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+ "policy_name": "gpt-6-astra",
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+ "base_seed": 206000000,
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+ "seed_policy": "episode_seed = base_seed + episode_index - 1",
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+ "randomization_recorded": true,
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+ "n_episodes": 10,
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+ "successes": 0,
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+ "error_count": 0,
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+ "evaluation_protocol": "reach_and_stop",
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+ "early_stop": true,
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+ "success_definition": "terminal.raw_condition holds for dwell_time_s",
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+ "measurement_window": "episode_start_to_stable_success_or_failure_budget",
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+ "max_episode_steps": 2985,
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+ "dwell_time_s": 0.5,
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+ "field_semantics": {
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+ "success_rate": "primary protocol success rate: stable_success for reach_and_stop; terminal at_end_success_budget for fixed_horizon",
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+ "avg_time_to_success_s": "main efficiency metric: mean time_to_stable_success_s over reached-success episodes",
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+ "task_efficiency": "benchmark-specific expert-normalized speed ratio: expert_time_s / time_to_stable_success_s over reached-success episodes",
21
+ "avg_steps_to_success": "diagnostic mean steps_to_stable_success over reached-success episodes, or None if no episode succeeds",
22
+ "avg_policy_steps_to_success": "diagnostic mean policy-rate control/action steps through stable success over reached-success episodes",
23
+ "avg_policy_queries_to_success": "diagnostic mean actual model inference queries through stable success over reached-success episodes; None when the first-success query count was not observed",
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+ "safe_success_rate": "episode success rate with no task-level hard safety violation (drop or tracked-object high speed; joint limits are diagnostic by default)",
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+ "hard_violation_rate": "episode rate with any task-level hard safety violation (drop or tracked-object high speed; joint limits are diagnostic by default)",
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+ "drop_rate": "episode rate with drop_off_table or drop_to_table_after_lift violation",
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+ "high_speed_violation_rate": "episode rate with any tracked object exceeding the configured speed threshold",
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+ "excessive_impact_rate": "deprecated contact-force impact metric; no longer populated by core safety",
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+ "robot_constraint_violation_rate": "diagnostic episode rate with any asset hard-joint-limit observation; excluded from safe_success_rate unless include_in_core_safety is explicitly enabled",
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+ "finger_joint_limit_saturation_rate": "episode rate with dexterous finger joints saturated beyond finger joint-limit thresholds; diagnostic by default and not included in safe_success_rate",
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+ "joint_limit_active_step_rate": "diagnostic mean fraction of steps with any joint exceeding the soft diagnostic margin",
32
+ "finger_joint_limit_saturation_step_rate": "diagnostic mean fraction of steps with finger joint-limit saturation",
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+ "max_joint_limit_excess_rad": "diagnostic maximum operating/soft-limit excess observed in radians; hard-limit source and role validation are in robot_constraint_diagnostics",
34
+ "safety_violation_rate_time": "compatibility diagnostic; with fixed physics_dt this is equivalent to safety_violation_step_rate and is omitted from grouped summary output",
35
+ "safety_violation_step_rate": "core safety metric: fraction of executed steps with task-level safety violations; joint-limit observations are excluded by default",
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+ "safety_violation_rate_event": "deprecated compatibility alias of safety_violation_events_per_step; omitted from grouped summary output",
37
+ "safety_violation_events_per_step": "diagnostic event density; may exceed 1 when multiple violations happen in one step",
38
+ "episode_violation_rate": "compatibility alias of hard_violation_rate; omitted from grouped core output",
39
+ "latched_stage_completion_rate": "main progress metric; ever-reached stage completion rate at episode end",
40
+ "current_stage_completion_rate": "diagnostic terminal-state stage completion rate at episode end",
41
+ "current_normalized_progress_score": "chain-depth diagnostic; normalized progress score at episode end",
42
+ "current_chain_depth_progress_score": "alias of current_normalized_progress_score for ordered dependency-depth diagnostics",
43
+ "latched_chain_depth_progress_score": "alias of latched_normalized_progress_score for ever-reached dependency-depth diagnostics",
44
+ "robustness": "success rates grouped by benchmark protocol category: cov, inv, and inv+cov"
45
+ }
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+ },
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+ "core_metrics": {
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+ "completion": {
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+ "success_rate": 0.0,
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+ "success_rate_ci": {
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+ "mean": 0.0,
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+ "ci_low": 0.0,
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+ "ci_high": 0.0
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+ }
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+ },
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+ "progress": {
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+ "latched_stage_completion_rate": 0.0
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+ },
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+ "efficiency": {
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+ "avg_time_to_success_s": null
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+ },
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+ "safety": {
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+ "safe_success_rate": 0.0,
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+ "hard_violation_rate": 0.8,
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+ "drop_rate": 0.8,
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+ "high_speed_violation_rate": 0.3,
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+ "safety_violation_step_rate": 0.03296482412060302
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+ },
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+ "robustness": {}
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+ },
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+ "diagnostic_metrics": {
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+ "completion": {
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+ "at_end_success_rate": 0.0,
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+ "task_family_success_rate": {
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+ "rigid_pick_place": 0.0
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+ }
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+ },
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+ "current_chain_depth_progress_score": 0.0,
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+ "latched_chain_depth_progress_score": 0.0,
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+ "avg_current_chain_depth": 0,
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+ "avg_latched_chain_depth": 0
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+ "expert_time_s": 33.15,
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+ "expert_time_step": 1989,
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+ "avg_policy_queries_to_success": null
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+ "violation_counts": {
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+ "drop_obj_163_baguette_5": 2,
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+ "drop_obj_182_bread_4": 1,
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+ "drop_to_table_obj_128_hamburg_3": 2,
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+ "drop_to_table_obj_163_baguette_5": 5,
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+ "drop_to_table_obj_182_bread_4": 7,
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+ "high_speed_distractor_01_clutter_006_mustard_bottle": 1,
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+ "high_speed_distractor_01_clutter_019_pitcher_base": 1,
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+ "high_speed_obj_163_baguette_5": 2,
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+ "high_speed_obj_182_bread_4": 1,
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+ "high_speed_obj_183_breadbasket_1": 2
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+ },
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+ "robot_constraint_violation_rate": 1.0,
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+ "finger_joint_limit_saturation_rate": 1.0,
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+ "joint_limit_active_step_rate": 0.17688442211055277,
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+ "finger_joint_limit_saturation_step_rate": 0.12254606365159129,
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+ "max_joint_limit_excess_rad": 3.084315538406372,
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+ "robot_constraint_diagnostics": {
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+ "joint_limit_soft_counts": {
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+ "left_index_dip_joint": 12,
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+ "left_index_mcp_joint": 32,
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+ "left_index_pip_joint": 24,
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+ "left_index_pitch_joint": 26,
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+ "left_middle_dip_joint": 8,
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+ "left_pinky_mcp_joint": 89,
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+ "left_ring_mcp_joint": 1,
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+ "left_ring_pip_joint": 78,
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+ "left_thumb_mcp_joint": 174,
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+ "left_thumb_pip_joint": 5,
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+ "right_index_pip_joint": 210,
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+ "right_index_pitch_joint": 1316,
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+ "right_middle_mcp_joint": 4,
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+ "right_middle_pip_joint": 701,
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+ "right_pinky_mcp_joint": 2924,
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+ "right_pinky_pip_joint": 511,
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+ "right_ring_dip_joint": 165,
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+ "right_ring_mcp_joint": 1679,
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+ "right_ring_pip_joint": 1189,
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+ "right_thumb_dip_joint": 130,
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+ "right_thumb_mcp_joint": 794,
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+ "right_thumb_pip_joint": 98
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+ },
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+ "joint_limit_hard_counts": {
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+ "left_index_mcp_joint": 1,
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+ "left_index_pip_joint": 5,
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+ "left_index_pitch_joint": 3,
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+ "left_middle_pip_joint": 2,
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+ "left_pinky_mcp_joint": 5,
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+ "left_ring_pip_joint": 6,
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+ "right_index_dip_joint": 1,
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+ "right_index_mcp_joint": 2,
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+ "right_index_pitch_joint": 30,
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+ "right_middle_pip_joint": 58,
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+ "right_pinky_dip_joint": 4,
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+ "right_pinky_pip_joint": 40,
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+ "right_ring_pip_joint": 151,
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+ "right_thumb_dip_joint": 5,
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+ "right_thumb_mcp_joint": 24,
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+ "right_thumb_pip_joint": 3,
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+ "right_thumb_yaw_joint": 2
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+ },
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+ "joint_limit_hard_episode_events": 170,
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+ "finger_joint_limit_saturation_counts": {
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+ "left_index_dip_joint": 3,
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+ "left_index_mcp_joint": 27,
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+ "left_index_pip_joint": 15,
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+ "left_index_pitch_joint": 2,
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+ "left_middle_pip_joint": 31,
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+ "left_pinky_mcp_joint": 50,
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+ "left_pinky_pip_joint": 5,
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+ "left_ring_pip_joint": 37,
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+ "right_middle_pip_joint": 314,
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+ "right_middle_pitch_joint": 631,
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+ "right_ring_dip_joint": 120,
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+ "right_thumb_pip_joint": 73
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+ },
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+ "joint_limit_max_excess_by_joint": {
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+ "left_index_dip_joint": 0.3007436990737915,
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+ "left_index_mcp_joint": 1.2541817426681519,
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+ "left_index_pip_joint": 0.5510872006416321,
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+ "left_middle_pip_joint": 0.9280629754066467,
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+ "left_middle_pitch_joint": 0.01650257222354412,
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+ "left_pinky_dip_joint": 1.1730775440810248e-05,
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+ "left_pinky_mcp_joint": 0.43559882044792175,
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+ "left_ring_pip_joint": 0.9072043895721436,
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+ "left_thumb_pip_joint": 0.18143272399902344,
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+ "left_thumb_yaw_joint": 0.00297143729403615,
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+ "right_index_dip_joint": 0.5543527603149414,
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+ "right_index_mcp_joint": 0.22716423869132996,
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+ "right_index_pip_joint": 1.683140516281128,
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+ "right_index_pitch_joint": 1.3602131605148315,
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+ "right_middle_dip_joint": 0.8403565883636475,
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+ "right_middle_mcp_joint": 0.0468006432056427,
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+ "right_middle_pip_joint": 3.084315538406372,
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+ "right_pinky_dip_joint": 0.08165574073791504,
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+ "right_pinky_pip_joint": 2.373507499694824,
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+ "right_ring_dip_joint": 1.5018227100372314,
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+ "right_ring_mcp_joint": 2.1126577854156494,
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+ "right_ring_pip_joint": 2.5233230590820312,
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+ "right_thumb_dip_joint": 1.1205986738204956,
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+ "right_thumb_mcp_joint": 1.225667953491211,
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+ "right_thumb_pip_joint": 1.7652851343154907,
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+ },
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+ "coverage": {
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+ "available": 10,
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+ "unknown": 0
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+ },
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+ "joint_role_manifest": {
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+ "available": 10,
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+ "unavailable": 0,
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+ "unknown": 0
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+ }
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+ },
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+ "hard_limit_sources": {
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+ "runtime.joint_pos_limits": 10
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+ },
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+ "soft_limit_sources": {
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+ "runtime.soft_joint_pos_limits": 10
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+ },
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+ "unknown_runtime_joint_names": [],
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+ "baseline_checks": {
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+ "post_home": {
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+ "checked": 10,
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+ "hard_violation_episodes": 0
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+ },
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+ "post_reset": {
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+ "checked": 10,
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+ "hard_violation_episodes": 0
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+ }
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+ }
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+ }
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+ },
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+ "robot_motion": {
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+ "joint_acceleration_rms": 42.03115120574183,
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+ "joint_effort_rms": 40.095110257162816,
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+ "joint_jerk_rms": 4255.74555520429,
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+ "joint_velocity_rms": 0.8570957403328379
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+ },
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+ "grasp": {
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+ "kinematic_grasp_stability_index": 0.9053341556108909,
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+ "mean_kinematic_grasp_stability": 0.45365309487160427,
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+ "per_object_best_kinematic_grasp_stability": {
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+ "obj_127_french_fries_2": 0.0005072203712319478,
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+ "obj_128_hamburg_3": 0.4519183539365257,
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+ "obj_163_baguette_5": 0.8854239570936067,
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+ "obj_182_bread_4": 0.727510702783414
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+ },
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+ "grasp_gsi_diagnostics": {
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+ "mean_anti_slip_score": 0.7374288107202726,
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+ "mean_duration_score": 0.3526976549413741,
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+ "mean_hold_score": 0.21971691792295156,
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+ "mean_kinematic_stability_score": 0.06098248369518157,
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+ "mean_legacy_gsi": 0.34845968288010737,
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+ "mean_lift_score": 0.2932328308207705,
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+ "mean_motion_stability_score": 0.20608393419595297
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+ }
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+ },
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+ "tool": {
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+ "tool_selection_accuracy": null,
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+ "tool_switch_success_rate": null,
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+ "tool_switch_total": 0,
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+ "tool_switch_successful": 0
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+ },
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+ "runtime": {
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+ "avg_steps": 2985,
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+ "error_count": 0
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+ }
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+ }
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+ }
gpt6_astra_1x_icl/per_task_eval/61_medicine_shoebox_pack/Full/per_episode.jsonl ADDED
The diff for this file is too large to render. See raw diff
 
gpt6_astra_1x_icl/per_task_eval/61_medicine_shoebox_pack/Full/summary.json ADDED
@@ -0,0 +1,217 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "metric_schema_version": "core-v1.8-policy-step-query-split",
3
+ "metadata": {
4
+ "policy_name": "gpt-6-astra",
5
+ "base_seed": 206100000,
6
+ "seed_policy": "episode_seed = base_seed + episode_index - 1",
7
+ "randomization_recorded": true,
8
+ "n_episodes": 10,
9
+ "successes": 8,
10
+ "error_count": 1,
11
+ "evaluation_protocol": "reach_and_stop",
12
+ "early_stop": true,
13
+ "success_definition": "terminal.raw_condition holds for dwell_time_s",
14
+ "measurement_window": "episode_start_to_stable_success_or_failure_budget",
15
+ "max_episode_steps": 3102,
16
+ "dwell_time_s": 0.5,
17
+ "field_semantics": {
18
+ "success_rate": "primary protocol success rate: stable_success for reach_and_stop; terminal at_end_success_budget for fixed_horizon",
19
+ "avg_time_to_success_s": "main efficiency metric: mean time_to_stable_success_s over reached-success episodes",
20
+ "task_efficiency": "benchmark-specific expert-normalized speed ratio: expert_time_s / time_to_stable_success_s over reached-success episodes",
21
+ "avg_steps_to_success": "diagnostic mean steps_to_stable_success over reached-success episodes, or None if no episode succeeds",
22
+ "avg_policy_steps_to_success": "diagnostic mean policy-rate control/action steps through stable success over reached-success episodes",
23
+ "avg_policy_queries_to_success": "diagnostic mean actual model inference queries through stable success over reached-success episodes; None when the first-success query count was not observed",
24
+ "safe_success_rate": "episode success rate with no task-level hard safety violation (drop or tracked-object high speed; joint limits are diagnostic by default)",
25
+ "hard_violation_rate": "episode rate with any task-level hard safety violation (drop or tracked-object high speed; joint limits are diagnostic by default)",
26
+ "drop_rate": "episode rate with drop_off_table or drop_to_table_after_lift violation",
27
+ "high_speed_violation_rate": "episode rate with any tracked object exceeding the configured speed threshold",
28
+ "excessive_impact_rate": "deprecated contact-force impact metric; no longer populated by core safety",
29
+ "robot_constraint_violation_rate": "diagnostic episode rate with any asset hard-joint-limit observation; excluded from safe_success_rate unless include_in_core_safety is explicitly enabled",
30
+ "finger_joint_limit_saturation_rate": "episode rate with dexterous finger joints saturated beyond finger joint-limit thresholds; diagnostic by default and not included in safe_success_rate",
31
+ "joint_limit_active_step_rate": "diagnostic mean fraction of steps with any joint exceeding the soft diagnostic margin",
32
+ "finger_joint_limit_saturation_step_rate": "diagnostic mean fraction of steps with finger joint-limit saturation",
33
+ "max_joint_limit_excess_rad": "diagnostic maximum operating/soft-limit excess observed in radians; hard-limit source and role validation are in robot_constraint_diagnostics",
34
+ "safety_violation_rate_time": "compatibility diagnostic; with fixed physics_dt this is equivalent to safety_violation_step_rate and is omitted from grouped summary output",
35
+ "safety_violation_step_rate": "core safety metric: fraction of executed steps with task-level safety violations; joint-limit observations are excluded by default",
36
+ "safety_violation_rate_event": "deprecated compatibility alias of safety_violation_events_per_step; omitted from grouped summary output",
37
+ "safety_violation_events_per_step": "diagnostic event density; may exceed 1 when multiple violations happen in one step",
38
+ "episode_violation_rate": "compatibility alias of hard_violation_rate; omitted from grouped core output",
39
+ "latched_stage_completion_rate": "main progress metric; ever-reached stage completion rate at episode end",
40
+ "current_stage_completion_rate": "diagnostic terminal-state stage completion rate at episode end",
41
+ "current_normalized_progress_score": "chain-depth diagnostic; normalized progress score at episode end",
42
+ "current_chain_depth_progress_score": "alias of current_normalized_progress_score for ordered dependency-depth diagnostics",
43
+ "latched_chain_depth_progress_score": "alias of latched_normalized_progress_score for ever-reached dependency-depth diagnostics",
44
+ "robustness": "success rates grouped by benchmark protocol category: cov, inv, and inv+cov"
45
+ }
46
+ },
47
+ "core_metrics": {
48
+ "completion": {
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+ "success_rate": 0.8,
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+ "success_rate_ci": {
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+ "mean": 0.8,
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+ "ci_low": 0.5,
53
+ "ci_high": 1.0
54
+ }
55
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+ "left_thumb_pip": 3,
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+ "right_index_mcp": 2,
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+ "soft_limit_sources": {
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+ "runtime.soft_joint_pos_limits": 10
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+ "baseline_checks": {
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+ "obj_211_hydrating_oil_4": 0.574519497127236,
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+ "obj_218_tooth_paste_3": 0.722047709770264
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+ }
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+ }
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+ }
gpt6_astra_1x_icl/per_task_eval/62_shoebox_accessory_pack/Full/per_episode.jsonl ADDED
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gpt6_astra_1x_icl/per_task_eval/62_shoebox_accessory_pack/Full/summary.json ADDED
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1
+ {
2
+ "metric_schema_version": "core-v1.8-policy-step-query-split",
3
+ "metadata": {
4
+ "policy_name": "gpt-6-astra",
5
+ "base_seed": 206200000,
6
+ "seed_policy": "episode_seed = base_seed + episode_index - 1",
7
+ "randomization_recorded": true,
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+ "n_episodes": 10,
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+ "successes": 1,
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+ "error_count": 1,
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+ "evaluation_protocol": "reach_and_stop",
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+ "early_stop": true,
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+ "success_definition": "terminal.raw_condition holds for dwell_time_s",
14
+ "measurement_window": "episode_start_to_stable_success_or_failure_budget",
15
+ "max_episode_steps": 3231,
16
+ "dwell_time_s": 0.5,
17
+ "field_semantics": {
18
+ "success_rate": "primary protocol success rate: stable_success for reach_and_stop; terminal at_end_success_budget for fixed_horizon",
19
+ "avg_time_to_success_s": "main efficiency metric: mean time_to_stable_success_s over reached-success episodes",
20
+ "task_efficiency": "benchmark-specific expert-normalized speed ratio: expert_time_s / time_to_stable_success_s over reached-success episodes",
21
+ "avg_steps_to_success": "diagnostic mean steps_to_stable_success over reached-success episodes, or None if no episode succeeds",
22
+ "avg_policy_steps_to_success": "diagnostic mean policy-rate control/action steps through stable success over reached-success episodes",
23
+ "avg_policy_queries_to_success": "diagnostic mean actual model inference queries through stable success over reached-success episodes; None when the first-success query count was not observed",
24
+ "safe_success_rate": "episode success rate with no task-level hard safety violation (drop or tracked-object high speed; joint limits are diagnostic by default)",
25
+ "hard_violation_rate": "episode rate with any task-level hard safety violation (drop or tracked-object high speed; joint limits are diagnostic by default)",
26
+ "drop_rate": "episode rate with drop_off_table or drop_to_table_after_lift violation",
27
+ "high_speed_violation_rate": "episode rate with any tracked object exceeding the configured speed threshold",
28
+ "excessive_impact_rate": "deprecated contact-force impact metric; no longer populated by core safety",
29
+ "robot_constraint_violation_rate": "diagnostic episode rate with any asset hard-joint-limit observation; excluded from safe_success_rate unless include_in_core_safety is explicitly enabled",
30
+ "finger_joint_limit_saturation_rate": "episode rate with dexterous finger joints saturated beyond finger joint-limit thresholds; diagnostic by default and not included in safe_success_rate",
31
+ "joint_limit_active_step_rate": "diagnostic mean fraction of steps with any joint exceeding the soft diagnostic margin",
32
+ "finger_joint_limit_saturation_step_rate": "diagnostic mean fraction of steps with finger joint-limit saturation",
33
+ "max_joint_limit_excess_rad": "diagnostic maximum operating/soft-limit excess observed in radians; hard-limit source and role validation are in robot_constraint_diagnostics",
34
+ "safety_violation_rate_time": "compatibility diagnostic; with fixed physics_dt this is equivalent to safety_violation_step_rate and is omitted from grouped summary output",
35
+ "safety_violation_step_rate": "core safety metric: fraction of executed steps with task-level safety violations; joint-limit observations are excluded by default",
36
+ "safety_violation_rate_event": "deprecated compatibility alias of safety_violation_events_per_step; omitted from grouped summary output",
37
+ "safety_violation_events_per_step": "diagnostic event density; may exceed 1 when multiple violations happen in one step",
38
+ "episode_violation_rate": "compatibility alias of hard_violation_rate; omitted from grouped core output",
39
+ "latched_stage_completion_rate": "main progress metric; ever-reached stage completion rate at episode end",
40
+ "current_stage_completion_rate": "diagnostic terminal-state stage completion rate at episode end",
41
+ "current_normalized_progress_score": "chain-depth diagnostic; normalized progress score at episode end",
42
+ "current_chain_depth_progress_score": "alias of current_normalized_progress_score for ordered dependency-depth diagnostics",
43
+ "latched_chain_depth_progress_score": "alias of latched_normalized_progress_score for ever-reached dependency-depth diagnostics",
44
+ "robustness": "success rates grouped by benchmark protocol category: cov, inv, and inv+cov"
45
+ }
46
+ },
47
+ "core_metrics": {
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+ "completion": {
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+ "success_rate": 0.1,
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+ "success_rate_ci": {
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+ "mean": 0.1,
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+ "ci_low": 0.0,
53
+ "ci_high": 0.3
54
+ }
55
+ },
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+ "progress": {
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+ "latched_stage_completion_rate": 0.5
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+ "efficiency": {
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+ "avg_time_to_success_s": 50.233333333331764
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+ },
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+ "safety": {
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+ "safe_success_rate": 0.1,
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+ "hard_violation_rate": 0.6,
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+ "drop_rate": 0.6,
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+ "high_speed_violation_rate": 0.2,
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+ "safety_violation_step_rate": 0.0008907657286133747
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+ "robustness": {}
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+ "diagnostic_metrics": {
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+ "at_end_success_rate": 0.1,
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+ "task_family_success_rate": {
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+ "rigid_pick_place": 0.1
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+ }
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81
+ "current_chain_depth_progress_score": 0.36666666666666664,
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+ "latched_chain_depth_progress_score": 0.5,
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+ "avg_current_chain_depth": 1.1,
84
+ "avg_latched_chain_depth": 1.5
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+ "efficiency": {
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+ "expert_time_s": 35.9,
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+ "expert_time_step": 2154,
90
+ "avg_steps_to_success": 3014,
91
+ "avg_policy_steps_to_success": 1005,
92
+ "avg_policy_queries_to_success": 22
93
+ },
94
+ "safety": {
95
+ "safety_violation_events_per_step": 0.00029692190953779156,
96
+ "violation_counts": {
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+ "drop_to_table_obj_143_pet_collar_3": 2,
98
+ "drop_to_table_obj_153_shoe_2": 1,
99
+ "drop_to_table_obj_203_seal_4": 4,
100
+ "high_speed_obj_129_shoe_box_1": 2
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+ },
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+ "robot_constraint_violation_rate": 1.0,
103
+ "finger_joint_limit_saturation_rate": 1.0,
104
+ "joint_limit_active_step_rate": 0.08284121276104385,
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+ "finger_joint_limit_saturation_step_rate": 0.041107188809343144,
106
+ "max_joint_limit_excess_rad": 1.3980273008346558,
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+ "robot_constraint_diagnostics": {
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+ "joint_limit_soft_counts": {
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+ "leap_l_10": 983,
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+ "leap_l_12": 1,
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+ "leap_l_15": 34,
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+ "leap_l_2": 88,
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+ "multi_leap_r_1": 37,
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+ "multi_leap_r_10": 55,
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+ "multi_leap_r_2": 1003,
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+ "multi_leap_r_5": 309,
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+ "multi_leap_r_6": 40,
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+ "multi_leap_r_9": 125
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+ "joint_limit_hard_counts": {
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+ "leap_l_1": 1,
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+ "leap_l_10": 112,
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+ "leap_l_12": 1,
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+ "leap_l_13": 1,
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+ "leap_l_2": 22,
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+ "leap_l_5": 3,
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+ "leap_l_6": 2,
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+ "multi_leap_r_1": 11,
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+ "multi_leap_r_9": 15
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+ "joint_limit_hard_episode_events": 286,
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+ "finger_joint_limit_saturation_counts": {
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+ "leap_l_10": 448,
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+ "leap_l_6": 33,
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+ "multi_leap_r_1": 23,
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+ "multi_leap_r_10": 6,
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+ "joint_limit_max_excess_by_joint": {
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+ "leap_l_1": 0.006041496992111206,
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+ "leap_l_10": 0.9413332939147949,
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+ "leap_l_11": 0.0007315278053283691,
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+ "leap_l_12": 0.030606746673583984,
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+ "leap_l_15": 0.07977128028869629,
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+ "leap_l_2": 0.14914929866790771,
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+ "multi_joint2": 8.726119995117188e-05,
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+ "joint_role_manifest": {
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+ },
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+ "hard_limit_sources": {
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+ "runtime.joint_pos_limits": 10
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+ },
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+ "soft_limit_sources": {
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+ "runtime.soft_joint_pos_limits": 10
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+ "unknown_runtime_joint_names": [],
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+ "baseline_checks": {
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+ "post_home": {
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+ "post_reset": {
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+ "checked": 10,
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+ "hard_violation_episodes": 0
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+ }
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+ }
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+ }
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+ },
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+ "robot_motion": {
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+ "joint_acceleration_rms": 13.450612894861683,
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+ "joint_effort_rms": 52.50730358736812,
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+ "joint_jerk_rms": 1317.9484685470466,
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+ "grasp": {
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+ "kinematic_grasp_stability_index": 0.8428762547557698,
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+ "mean_kinematic_grasp_stability": 0.42899256368516175,
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+ "per_object_best_kinematic_grasp_stability": {
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+ "obj_143_pet_collar_3": 0.3203506381371494,
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+ "obj_153_shoe_2": 0.534497211861279,
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+ "obj_203_seal_4": 0.734455183686091
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+ },
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+ "grasp_gsi_diagnostics": {
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+ "mean_anti_slip_score": 0.8422642140748882,
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+ "mean_duration_score": 0.34615112041520985,
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+ "mean_hold_score": 0.08341946009800057,
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+ "mean_kinematic_stability_score": 0.04143370823434997,
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+ "mean_legacy_gsi": 0.28596229946024676,
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+ "mean_lift_score": 0.11013936975425967,
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+ "mean_motion_stability_score": 0.07251795644534301
224
+ }
225
+ },
226
+ "tool": {
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+ "tool_selection_accuracy": null,
228
+ "tool_switch_success_rate": null,
229
+ "tool_switch_total": 0,
230
+ "tool_switch_successful": 0
231
+ },
232
+ "runtime": {
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+ "avg_steps": 3031.1,
234
+ "error_count": 1
235
+ }
236
+ }
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+ }
gpt6_astra_1x_icl/per_task_eval/64_sports_ball_cup_sort/Full/per_episode.jsonl ADDED
The diff for this file is too large to render. See raw diff
 
gpt6_astra_1x_icl/per_task_eval/64_sports_ball_cup_sort/Full/summary.json ADDED
@@ -0,0 +1,226 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
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+ "metric_schema_version": "core-v1.8-policy-step-query-split",
3
+ "metadata": {
4
+ "policy_name": "gpt-6-astra",
5
+ "base_seed": 206400000,
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+ "seed_policy": "episode_seed = base_seed + episode_index - 1",
7
+ "randomization_recorded": true,
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+ "evaluation_protocol": "reach_and_stop",
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+ "early_stop": true,
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+ "success_definition": "terminal.raw_condition holds for dwell_time_s",
14
+ "measurement_window": "episode_start_to_stable_success_or_failure_budget",
15
+ "max_episode_steps": 1995,
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+ "dwell_time_s": 0.5,
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+ "field_semantics": {
18
+ "success_rate": "primary protocol success rate: stable_success for reach_and_stop; terminal at_end_success_budget for fixed_horizon",
19
+ "avg_time_to_success_s": "main efficiency metric: mean time_to_stable_success_s over reached-success episodes",
20
+ "task_efficiency": "benchmark-specific expert-normalized speed ratio: expert_time_s / time_to_stable_success_s over reached-success episodes",
21
+ "avg_steps_to_success": "diagnostic mean steps_to_stable_success over reached-success episodes, or None if no episode succeeds",
22
+ "avg_policy_steps_to_success": "diagnostic mean policy-rate control/action steps through stable success over reached-success episodes",
23
+ "avg_policy_queries_to_success": "diagnostic mean actual model inference queries through stable success over reached-success episodes; None when the first-success query count was not observed",
24
+ "safe_success_rate": "episode success rate with no task-level hard safety violation (drop or tracked-object high speed; joint limits are diagnostic by default)",
25
+ "hard_violation_rate": "episode rate with any task-level hard safety violation (drop or tracked-object high speed; joint limits are diagnostic by default)",
26
+ "drop_rate": "episode rate with drop_off_table or drop_to_table_after_lift violation",
27
+ "high_speed_violation_rate": "episode rate with any tracked object exceeding the configured speed threshold",
28
+ "excessive_impact_rate": "deprecated contact-force impact metric; no longer populated by core safety",
29
+ "robot_constraint_violation_rate": "diagnostic episode rate with any asset hard-joint-limit observation; excluded from safe_success_rate unless include_in_core_safety is explicitly enabled",
30
+ "finger_joint_limit_saturation_rate": "episode rate with dexterous finger joints saturated beyond finger joint-limit thresholds; diagnostic by default and not included in safe_success_rate",
31
+ "joint_limit_active_step_rate": "diagnostic mean fraction of steps with any joint exceeding the soft diagnostic margin",
32
+ "finger_joint_limit_saturation_step_rate": "diagnostic mean fraction of steps with finger joint-limit saturation",
33
+ "max_joint_limit_excess_rad": "diagnostic maximum operating/soft-limit excess observed in radians; hard-limit source and role validation are in robot_constraint_diagnostics",
34
+ "safety_violation_rate_time": "compatibility diagnostic; with fixed physics_dt this is equivalent to safety_violation_step_rate and is omitted from grouped summary output",
35
+ "safety_violation_step_rate": "core safety metric: fraction of executed steps with task-level safety violations; joint-limit observations are excluded by default",
36
+ "safety_violation_rate_event": "deprecated compatibility alias of safety_violation_events_per_step; omitted from grouped summary output",
37
+ "safety_violation_events_per_step": "diagnostic event density; may exceed 1 when multiple violations happen in one step",
38
+ "episode_violation_rate": "compatibility alias of hard_violation_rate; omitted from grouped core output",
39
+ "latched_stage_completion_rate": "main progress metric; ever-reached stage completion rate at episode end",
40
+ "current_stage_completion_rate": "diagnostic terminal-state stage completion rate at episode end",
41
+ "current_normalized_progress_score": "chain-depth diagnostic; normalized progress score at episode end",
42
+ "current_chain_depth_progress_score": "alias of current_normalized_progress_score for ordered dependency-depth diagnostics",
43
+ "latched_chain_depth_progress_score": "alias of latched_normalized_progress_score for ever-reached dependency-depth diagnostics",
44
+ "robustness": "success rates grouped by benchmark protocol category: cov, inv, and inv+cov"
45
+ }
46
+ },
47
+ "core_metrics": {
48
+ "completion": {
49
+ "success_rate": 0.6,
50
+ "success_rate_ci": {
51
+ "mean": 0.6,
52
+ "ci_low": 0.3,
53
+ "ci_high": 0.9
54
+ }
55
+ },
56
+ "progress": {
57
+ "latched_stage_completion_rate": 0.725
58
+ },
59
+ "efficiency": {
60
+ "avg_time_to_success_s": 32.62777777777721
61
+ },
62
+ "safety": {
63
+ "safe_success_rate": 0.6,
64
+ "hard_violation_rate": 0.3,
65
+ "drop_rate": 0.3,
66
+ "high_speed_violation_rate": 0.1,
67
+ "safety_violation_step_rate": 0.00035486160397445
68
+ },
69
+ "robustness": {}
70
+ },
71
+ "diagnostic_metrics": {
72
+ "completion": {
73
+ "ever_instant_success_rate": 0.7,
74
+ "at_end_success_rate": 0.6,
75
+ "task_family_success_rate": {
76
+ "rigid_pick_place": 0.6
77
+ }
78
+ },
79
+ "progress": {
80
+ "current_stage_completion_rate": 0.675,
81
+ "current_chain_depth_progress_score": 0.725,
82
+ "latched_chain_depth_progress_score": 0.725,
83
+ "avg_current_chain_depth": 2.9,
84
+ "avg_latched_chain_depth": 2.9
85
+ },
86
+ "efficiency": {
87
+ "task_efficiency": 0.6789434557829453,
88
+ "expert_time_s": 22.15,
89
+ "expert_time_step": 1329,
90
+ "avg_steps_to_success": 1957.6666666666667,
91
+ "avg_policy_steps_to_success": 652.8333333333334,
92
+ "avg_policy_queries_to_success": 30.5
93
+ },
94
+ "safety": {
95
+ "safety_violation_events_per_step": 0.00035486160397445,
96
+ "violation_counts": {
97
+ "drop_to_table_obj_055_baseball_4": 3,
98
+ "drop_to_table_obj_057_racquetball_5": 2,
99
+ "drop_to_table_obj_058_golf_ball_6": 1,
100
+ "high_speed_obj_055_baseball_4": 1
101
+ },
102
+ "robot_constraint_violation_rate": 0.9,
103
+ "finger_joint_limit_saturation_rate": 0.4,
104
+ "joint_limit_active_step_rate": 0.027324343506032647,
105
+ "finger_joint_limit_saturation_step_rate": 0.01333265740646862,
106
+ "max_joint_limit_excess_rad": 0.8996438980102539,
107
+ "robot_constraint_diagnostics": {
108
+ "joint_limit_soft_counts": {
109
+ "joint_10_0": 265,
110
+ "multi_joint_2_0": 106,
111
+ "multi_joint_6_0": 15,
112
+ "multi_joint_7_0": 45,
113
+ "multi_joint_9_0": 87,
114
+ "multi_panda_joint5": 18,
115
+ "panda_joint7": 35
116
+ },
117
+ "joint_limit_hard_counts": {
118
+ "joint_10_0": 22,
119
+ "joint_12_0": 1,
120
+ "joint_9_0": 1,
121
+ "multi_joint_1_0": 1,
122
+ "multi_joint_2_0": 73,
123
+ "multi_joint_5_0": 4,
124
+ "multi_joint_6_0": 1,
125
+ "multi_joint_7_0": 2,
126
+ "multi_joint_9_0": 3,
127
+ "multi_panda_joint5": 1,
128
+ "panda_joint7": 2
129
+ },
130
+ "joint_limit_hard_episode_events": 108,
131
+ "finger_joint_limit_saturation_counts": {
132
+ "joint_10_0": 184,
133
+ "multi_joint_2_0": 24,
134
+ "multi_joint_7_0": 11,
135
+ "multi_joint_9_0": 44
136
+ },
137
+ "joint_limit_max_excess_by_joint": {
138
+ "joint_10_0": 0.66518634557724,
139
+ "joint_12_0": 0.0050629377365112305,
140
+ "joint_13_0": 3.2261013984680176e-06,
141
+ "joint_1_0": 0.00023233890533447266,
142
+ "joint_2_0": 0.0004210472106933594,
143
+ "joint_5_0": 0.00020384788513183594,
144
+ "joint_6_0": 0.0002518892288208008,
145
+ "joint_9_0": 0.006655454635620117,
146
+ "multi_joint_10_0": 0.001398324966430664,
147
+ "multi_joint_1_0": 0.007284760475158691,
148
+ "multi_joint_2_0": 0.8996438980102539,
149
+ "multi_joint_5_0": 0.006478667259216309,
150
+ "multi_joint_6_0": 0.04621243476867676,
151
+ "multi_joint_7_0": 0.24186664819717407,
152
+ "multi_joint_9_0": 0.22497618198394775,
153
+ "multi_panda_joint1": 7.200241088867188e-05,
154
+ "multi_panda_joint5": 0.06462550163269043,
155
+ "multi_panda_joint7": 0.0021522045135498047,
156
+ "panda_joint5": 0.0001461505889892578,
157
+ "panda_joint7": 0.08028483390808105
158
+ },
159
+ "coverage": {
160
+ "hard_limit_source": {
161
+ "available": 10,
162
+ "unavailable": 0,
163
+ "unknown": 0
164
+ },
165
+ "joint_role_manifest": {
166
+ "available": 10,
167
+ "unavailable": 0,
168
+ "unknown": 0
169
+ }
170
+ },
171
+ "hard_limit_sources": {
172
+ "runtime.joint_pos_limits": 10
173
+ },
174
+ "soft_limit_sources": {
175
+ "runtime.soft_joint_pos_limits": 10
176
+ },
177
+ "unknown_runtime_joint_names": [],
178
+ "baseline_checks": {
179
+ "post_home": {
180
+ "checked": 10,
181
+ "hard_violation_episodes": 0
182
+ },
183
+ "post_reset": {
184
+ "checked": 10,
185
+ "hard_violation_episodes": 0
186
+ }
187
+ }
188
+ }
189
+ },
190
+ "robot_motion": {
191
+ "joint_acceleration_rms": 9.207911887023146,
192
+ "joint_effort_rms": 29.024835436637847,
193
+ "joint_jerk_rms": 927.7374989751764,
194
+ "joint_velocity_rms": 0.2729033813019237
195
+ },
196
+ "grasp": {
197
+ "kinematic_grasp_stability_index": 0.9867421040812419,
198
+ "mean_kinematic_grasp_stability": 0.40980121245964235,
199
+ "per_object_best_kinematic_grasp_stability": {
200
+ "obj_054_softball_3": 0.6421239324384325,
201
+ "obj_055_baseball_4": 0.9296671411791132,
202
+ "obj_057_racquetball_5": 0.8341595343153546,
203
+ "obj_058_golf_ball_6": 0.737731666754543
204
+ },
205
+ "grasp_gsi_diagnostics": {
206
+ "mean_anti_slip_score": 0.8336579913254804,
207
+ "mean_duration_score": 0.31413740111441035,
208
+ "mean_hold_score": 0.24307938818638286,
209
+ "mean_kinematic_stability_score": 0.09424760398579528,
210
+ "mean_legacy_gsi": 0.3746012329278188,
211
+ "mean_lift_score": 0.3328560603057352,
212
+ "mean_motion_stability_score": 0.227613904503579
213
+ }
214
+ },
215
+ "tool": {
216
+ "tool_selection_accuracy": null,
217
+ "tool_switch_success_rate": null,
218
+ "tool_switch_total": 0,
219
+ "tool_switch_successful": 0
220
+ },
221
+ "runtime": {
222
+ "avg_steps": 1972.6,
223
+ "error_count": 0
224
+ }
225
+ }
226
+ }
gpt6_astra_1x_icl/per_task_eval/67_faucet_cup_water_fill/Full/per_episode.jsonl ADDED
The diff for this file is too large to render. See raw diff
 
gpt6_astra_1x_icl/per_task_eval/67_faucet_cup_water_fill/Full/summary.json ADDED
@@ -0,0 +1,255 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "metric_schema_version": "core-v1.8-policy-step-query-split",
3
+ "metadata": {
4
+ "policy_name": "gpt-6-astra",
5
+ "base_seed": 206700000,
6
+ "seed_policy": "episode_seed = base_seed + episode_index - 1",
7
+ "randomization_recorded": true,
8
+ "n_episodes": 10,
9
+ "successes": 1,
10
+ "error_count": 0,
11
+ "evaluation_protocol": "reach_and_stop",
12
+ "early_stop": true,
13
+ "success_definition": "terminal.raw_condition holds for dwell_time_s",
14
+ "measurement_window": "episode_start_to_stable_success_or_failure_budget",
15
+ "max_episode_steps": 2892,
16
+ "dwell_time_s": 3.0,
17
+ "field_semantics": {
18
+ "success_rate": "primary protocol success rate: stable_success for reach_and_stop; terminal at_end_success_budget for fixed_horizon",
19
+ "avg_time_to_success_s": "main efficiency metric: mean time_to_stable_success_s over reached-success episodes",
20
+ "task_efficiency": "benchmark-specific expert-normalized speed ratio: expert_time_s / time_to_stable_success_s over reached-success episodes",
21
+ "avg_steps_to_success": "diagnostic mean steps_to_stable_success over reached-success episodes, or None if no episode succeeds",
22
+ "avg_policy_steps_to_success": "diagnostic mean policy-rate control/action steps through stable success over reached-success episodes",
23
+ "avg_policy_queries_to_success": "diagnostic mean actual model inference queries through stable success over reached-success episodes; None when the first-success query count was not observed",
24
+ "safe_success_rate": "episode success rate with no task-level hard safety violation (drop or tracked-object high speed; joint limits are diagnostic by default)",
25
+ "hard_violation_rate": "episode rate with any task-level hard safety violation (drop or tracked-object high speed; joint limits are diagnostic by default)",
26
+ "drop_rate": "episode rate with drop_off_table or drop_to_table_after_lift violation",
27
+ "high_speed_violation_rate": "episode rate with any tracked object exceeding the configured speed threshold",
28
+ "excessive_impact_rate": "deprecated contact-force impact metric; no longer populated by core safety",
29
+ "robot_constraint_violation_rate": "diagnostic episode rate with any asset hard-joint-limit observation; excluded from safe_success_rate unless include_in_core_safety is explicitly enabled",
30
+ "finger_joint_limit_saturation_rate": "episode rate with dexterous finger joints saturated beyond finger joint-limit thresholds; diagnostic by default and not included in safe_success_rate",
31
+ "joint_limit_active_step_rate": "diagnostic mean fraction of steps with any joint exceeding the soft diagnostic margin",
32
+ "finger_joint_limit_saturation_step_rate": "diagnostic mean fraction of steps with finger joint-limit saturation",
33
+ "max_joint_limit_excess_rad": "diagnostic maximum operating/soft-limit excess observed in radians; hard-limit source and role validation are in robot_constraint_diagnostics",
34
+ "safety_violation_rate_time": "compatibility diagnostic; with fixed physics_dt this is equivalent to safety_violation_step_rate and is omitted from grouped summary output",
35
+ "safety_violation_step_rate": "core safety metric: fraction of executed steps with task-level safety violations; joint-limit observations are excluded by default",
36
+ "safety_violation_rate_event": "deprecated compatibility alias of safety_violation_events_per_step; omitted from grouped summary output",
37
+ "safety_violation_events_per_step": "diagnostic event density; may exceed 1 when multiple violations happen in one step",
38
+ "episode_violation_rate": "compatibility alias of hard_violation_rate; omitted from grouped core output",
39
+ "latched_stage_completion_rate": "main progress metric; ever-reached stage completion rate at episode end",
40
+ "current_stage_completion_rate": "diagnostic terminal-state stage completion rate at episode end",
41
+ "current_normalized_progress_score": "chain-depth diagnostic; normalized progress score at episode end",
42
+ "current_chain_depth_progress_score": "alias of current_normalized_progress_score for ordered dependency-depth diagnostics",
43
+ "latched_chain_depth_progress_score": "alias of latched_normalized_progress_score for ever-reached dependency-depth diagnostics",
44
+ "robustness": "success rates grouped by benchmark protocol category: cov, inv, and inv+cov"
45
+ }
46
+ },
47
+ "core_metrics": {
48
+ "completion": {
49
+ "success_rate": 0.1,
50
+ "success_rate_ci": {
51
+ "mean": 0.1,
52
+ "ci_low": 0.0,
53
+ "ci_high": 0.3
54
+ }
55
+ },
56
+ "progress": {
57
+ "latched_stage_completion_rate": 0.4
58
+ },
59
+ "efficiency": {
60
+ "avg_time_to_success_s": 42.46666666666554
61
+ },
62
+ "safety": {
63
+ "safe_success_rate": 0.1,
64
+ "hard_violation_rate": 0.7,
65
+ "drop_rate": 0.7,
66
+ "high_speed_violation_rate": 0.0,
67
+ "safety_violation_step_rate": 0.00024496080627099665
68
+ },
69
+ "robustness": {}
70
+ },
71
+ "diagnostic_metrics": {
72
+ "completion": {
73
+ "ever_instant_success_rate": 0.1,
74
+ "at_end_success_rate": 0.1,
75
+ "task_family_success_rate": {
76
+ "articulation_multi": 0.1
77
+ }
78
+ },
79
+ "progress": {
80
+ "current_stage_completion_rate": 0.15,
81
+ "current_chain_depth_progress_score": 0.25,
82
+ "latched_chain_depth_progress_score": 0.4,
83
+ "avg_current_chain_depth": 1,
84
+ "avg_latched_chain_depth": 1.6
85
+ },
86
+ "efficiency": {
87
+ "task_efficiency": 0.7566718995290624,
88
+ "expert_time_s": 32.13333333333333,
89
+ "expert_time_step": 1928,
90
+ "avg_steps_to_success": 2548,
91
+ "avg_policy_steps_to_success": 850,
92
+ "avg_policy_queries_to_success": 28
93
+ },
94
+ "safety": {
95
+ "safety_violation_events_per_step": 0.00024496080627099665,
96
+ "violation_counts": {
97
+ "drop_to_table_obj_031_spoon_1": 7
98
+ },
99
+ "robot_constraint_violation_rate": 1.0,
100
+ "finger_joint_limit_saturation_rate": 0.6,
101
+ "joint_limit_active_step_rate": 0.021871500559910415,
102
+ "finger_joint_limit_saturation_step_rate": 0.00566909294512878,
103
+ "max_joint_limit_excess_rad": 1.2255189418792725,
104
+ "robot_constraint_diagnostics": {
105
+ "joint_limit_soft_counts": {
106
+ "l_joint4": 69,
107
+ "left_index_proximal_joint": 101,
108
+ "left_middle_distal_joint": 34,
109
+ "left_middle_proximal_joint": 62,
110
+ "left_pinky_distal_joint": 38,
111
+ "left_pinky_proximal_joint": 10,
112
+ "left_ring_distal_joint": 11,
113
+ "left_ring_proximal_joint": 141,
114
+ "left_thumb_distal_joint": 57,
115
+ "left_thumb_metacarpal_joint": 11,
116
+ "left_thumb_proximal_joint": 32,
117
+ "right_index_proximal_joint": 9,
118
+ "right_middle_distal_joint": 45,
119
+ "right_middle_proximal_joint": 73,
120
+ "right_pinky_proximal_joint": 108,
121
+ "right_ring_distal_joint": 12,
122
+ "right_ring_proximal_joint": 68,
123
+ "right_thumb_metacarpal_joint": 93,
124
+ "right_thumb_proximal_joint": 72
125
+ },
126
+ "joint_limit_hard_counts": {
127
+ "l_joint4": 1,
128
+ "left_index_proximal_joint": 31,
129
+ "left_middle_distal_joint": 4,
130
+ "left_middle_proximal_joint": 32,
131
+ "left_pinky_distal_joint": 3,
132
+ "left_pinky_proximal_joint": 23,
133
+ "left_ring_distal_joint": 8,
134
+ "left_ring_proximal_joint": 29,
135
+ "left_thumb_distal_joint": 6,
136
+ "left_thumb_metacarpal_joint": 3,
137
+ "left_thumb_proximal_joint": 6,
138
+ "right_index_proximal_joint": 11,
139
+ "right_middle_distal_joint": 1,
140
+ "right_middle_proximal_joint": 10,
141
+ "right_pinky_distal_joint": 2,
142
+ "right_pinky_proximal_joint": 26,
143
+ "right_ring_distal_joint": 2,
144
+ "right_ring_proximal_joint": 12,
145
+ "right_thumb_distal_joint": 6,
146
+ "right_thumb_metacarpal_joint": 2,
147
+ "right_thumb_proximal_joint": 2
148
+ },
149
+ "joint_limit_hard_episode_events": 116,
150
+ "finger_joint_limit_saturation_counts": {
151
+ "left_index_proximal_joint": 21,
152
+ "left_middle_proximal_joint": 8,
153
+ "left_pinky_distal_joint": 7,
154
+ "left_ring_proximal_joint": 1,
155
+ "left_thumb_distal_joint": 43,
156
+ "left_thumb_proximal_joint": 11,
157
+ "right_middle_distal_joint": 37,
158
+ "right_middle_proximal_joint": 60,
159
+ "right_pinky_proximal_joint": 58,
160
+ "right_ring_proximal_joint": 62,
161
+ "right_thumb_metacarpal_joint": 73,
162
+ "right_thumb_proximal_joint": 66
163
+ },
164
+ "joint_limit_max_excess_by_joint": {
165
+ "joint3": 0.0006670951843261719,
166
+ "l_joint4": 0.6398665904998779,
167
+ "left_index_distal_joint": 7.247085598294234e-09,
168
+ "left_index_proximal_joint": 0.21345362067222595,
169
+ "left_middle_distal_joint": 0.0739472284913063,
170
+ "left_middle_proximal_joint": 0.49430060386657715,
171
+ "left_pinky_distal_joint": 0.18549209833145142,
172
+ "left_pinky_proximal_joint": 0.052287131547927856,
173
+ "left_ring_distal_joint": 0.08776852488517761,
174
+ "left_ring_proximal_joint": 0.27737730741500854,
175
+ "left_thumb_distal_joint": 0.5415257215499878,
176
+ "left_thumb_metacarpal_joint": 0.14287704229354858,
177
+ "left_thumb_proximal_joint": 0.19011513888835907,
178
+ "right_index_distal_joint": 3.43435807570458e-10,
179
+ "right_index_proximal_joint": 0.044638969004154205,
180
+ "right_middle_distal_joint": 0.5703709125518799,
181
+ "right_middle_proximal_joint": 1.2255189418792725,
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+ "right_pinky_distal_joint": 0.006779804825782776,
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+ "right_pinky_proximal_joint": 0.4822751581668854,
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+ "right_ring_distal_joint": 0.07349101454019547,
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+ "right_ring_proximal_joint": 0.729503333568573,
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+ "right_thumb_distal_joint": 0.006306767463684082,
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+ "right_thumb_metacarpal_joint": 1.004553198814392,
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+ "right_thumb_proximal_joint": 0.3518408536911011
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+ },
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+ "coverage": {
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+ "joint_role_manifest": {
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+ "hard_limit_sources": {
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+ "runtime.joint_pos_limits": 10
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+ "soft_limit_sources": {
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+ "runtime.soft_joint_pos_limits": 10
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+ },
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+ "unknown_runtime_joint_names": [],
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+ "baseline_checks": {
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+ "post_home": {
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+ "hard_violation_episodes": 0
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+ }
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+ }
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+ },
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+ "robot_motion": {
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+ "joint_effort_rms": 34.88281651243846,
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+ "joint_jerk_rms": 1792.867224072184,
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+ "mean_kinematic_grasp_stability": 0.2994397114519785,
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+ "per_object_best_kinematic_grasp_stability": {
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+ "obj_025_mug_1": 0.5855821488893681,
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+ "obj_031_spoon_1": 0.7227022694059623
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+ "error_count": 0
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+ }
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+ }
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+ }
gpt6_astra_1x_icl/per_task_eval/73_jigsaw_puzzle_assembly/Full/per_episode.jsonl ADDED
The diff for this file is too large to render. See raw diff
 
gpt6_astra_1x_icl/per_task_eval/73_jigsaw_puzzle_assembly/Full/summary.json ADDED
@@ -0,0 +1,329 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "metric_schema_version": "core-v1.8-policy-step-query-split",
3
+ "metadata": {
4
+ "policy_name": "gpt-6-astra",
5
+ "base_seed": 207300000,
6
+ "seed_policy": "episode_seed = base_seed + episode_index - 1",
7
+ "randomization_recorded": true,
8
+ "n_episodes": 10,
9
+ "successes": 0,
10
+ "error_count": 0,
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+ "evaluation_protocol": "reach_and_stop",
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+ "early_stop": true,
13
+ "success_definition": "terminal.raw_condition holds for dwell_time_s",
14
+ "measurement_window": "episode_start_to_stable_success_or_failure_budget",
15
+ "max_episode_steps": 3639,
16
+ "dwell_time_s": 0.5,
17
+ "field_semantics": {
18
+ "success_rate": "primary protocol success rate: stable_success for reach_and_stop; terminal at_end_success_budget for fixed_horizon",
19
+ "avg_time_to_success_s": "main efficiency metric: mean time_to_stable_success_s over reached-success episodes",
20
+ "task_efficiency": "benchmark-specific expert-normalized speed ratio: expert_time_s / time_to_stable_success_s over reached-success episodes",
21
+ "avg_steps_to_success": "diagnostic mean steps_to_stable_success over reached-success episodes, or None if no episode succeeds",
22
+ "avg_policy_steps_to_success": "diagnostic mean policy-rate control/action steps through stable success over reached-success episodes",
23
+ "avg_policy_queries_to_success": "diagnostic mean actual model inference queries through stable success over reached-success episodes; None when the first-success query count was not observed",
24
+ "safe_success_rate": "episode success rate with no task-level hard safety violation (drop or tracked-object high speed; joint limits are diagnostic by default)",
25
+ "hard_violation_rate": "episode rate with any task-level hard safety violation (drop or tracked-object high speed; joint limits are diagnostic by default)",
26
+ "drop_rate": "episode rate with drop_off_table or drop_to_table_after_lift violation",
27
+ "high_speed_violation_rate": "episode rate with any tracked object exceeding the configured speed threshold",
28
+ "excessive_impact_rate": "deprecated contact-force impact metric; no longer populated by core safety",
29
+ "robot_constraint_violation_rate": "diagnostic episode rate with any asset hard-joint-limit observation; excluded from safe_success_rate unless include_in_core_safety is explicitly enabled",
30
+ "finger_joint_limit_saturation_rate": "episode rate with dexterous finger joints saturated beyond finger joint-limit thresholds; diagnostic by default and not included in safe_success_rate",
31
+ "joint_limit_active_step_rate": "diagnostic mean fraction of steps with any joint exceeding the soft diagnostic margin",
32
+ "finger_joint_limit_saturation_step_rate": "diagnostic mean fraction of steps with finger joint-limit saturation",
33
+ "max_joint_limit_excess_rad": "diagnostic maximum operating/soft-limit excess observed in radians; hard-limit source and role validation are in robot_constraint_diagnostics",
34
+ "safety_violation_rate_time": "compatibility diagnostic; with fixed physics_dt this is equivalent to safety_violation_step_rate and is omitted from grouped summary output",
35
+ "safety_violation_step_rate": "core safety metric: fraction of executed steps with task-level safety violations; joint-limit observations are excluded by default",
36
+ "safety_violation_rate_event": "deprecated compatibility alias of safety_violation_events_per_step; omitted from grouped summary output",
37
+ "safety_violation_events_per_step": "diagnostic event density; may exceed 1 when multiple violations happen in one step",
38
+ "episode_violation_rate": "compatibility alias of hard_violation_rate; omitted from grouped core output",
39
+ "latched_stage_completion_rate": "main progress metric; ever-reached stage completion rate at episode end",
40
+ "current_stage_completion_rate": "diagnostic terminal-state stage completion rate at episode end",
41
+ "current_normalized_progress_score": "chain-depth diagnostic; normalized progress score at episode end",
42
+ "current_chain_depth_progress_score": "alias of current_normalized_progress_score for ordered dependency-depth diagnostics",
43
+ "latched_chain_depth_progress_score": "alias of latched_normalized_progress_score for ever-reached dependency-depth diagnostics",
44
+ "robustness": "success rates grouped by benchmark protocol category: cov, inv, and inv+cov"
45
+ }
46
+ },
47
+ "core_metrics": {
48
+ "completion": {
49
+ "success_rate": 0.0,
50
+ "success_rate_ci": {
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+ "mean": 0.0,
52
+ "ci_low": 0.0,
53
+ "ci_high": 0.0
54
+ }
55
+ },
56
+ "progress": {
57
+ "latched_stage_completion_rate": 0.2
58
+ },
59
+ "efficiency": {
60
+ "avg_time_to_success_s": null
61
+ },
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+ "safety": {
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+ "safe_success_rate": 0.0,
64
+ "hard_violation_rate": 0.3,
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+ "drop_rate": 0.3,
66
+ "high_speed_violation_rate": 0.0,
67
+ "safety_violation_step_rate": 0.00010992030777686178
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+ },
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+ "robustness": {}
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+ },
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+ "diagnostic_metrics": {
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+ "completion": {
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+ "ever_instant_success_rate": 0.0,
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+ "at_end_success_rate": 0.0,
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+ "task_family_success_rate": {
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+ "tetris_block_manipulation": 0.0
77
+ }
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+ },
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+ "progress": {
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+ "current_stage_completion_rate": 0.025,
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+ "current_chain_depth_progress_score": 0.1,
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+ "latched_chain_depth_progress_score": 0.7,
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+ "avg_current_chain_depth": 0.1,
84
+ "avg_latched_chain_depth": 0.7
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+ },
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+ "efficiency": {
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+ "expert_time_step": 2426,
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+ "avg_steps_to_success": null,
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+ "avg_policy_steps_to_success": null,
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+ "avg_policy_queries_to_success": null
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+ },
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+ "safety": {
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+ "violation_counts": {
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+ "drop_to_table_obj_326_piece_2": 3,
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+ "drop_to_table_obj_326_piece_3": 1,
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+ "drop_to_table_obj_326_piece_5": 1
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+ "robot_constraint_violation_rate": 1.0,
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+ "finger_joint_limit_saturation_rate": 0.9,
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+ "joint_limit_active_step_rate": 0.05798296235229459,
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+ "finger_joint_limit_saturation_step_rate": 0.027892278098378676,
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+ "max_joint_limit_excess_rad": 1.9653520584106445,
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+ "robot_constraint_diagnostics": {
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+ "joint_limit_soft_counts": {
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+ "multi_A7": 172,
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+ "multi_right_index_DIP": 275,
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+ "multi_right_middle_PIP": 181,
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+ "multi_right_ring_DIP": 189,
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+ "joint_limit_hard_counts": {
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+ "joint_limit_hard_episode_events": 100,
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+ "unknown_runtime_joint_names": [],
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+ "baseline_checks": {
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+ "robot_motion": {
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+ "per_object_best_kinematic_grasp_stability": {
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+ },
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+ "grasp_gsi_diagnostics": {
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+ "mean_anti_slip_score": 0.9893395621507682,
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+ "mean_duration_score": 0.05450929742603283,
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+ "mean_hold_score": 0.010514152239626385,
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+ "mean_kinematic_stability_score": 0.005262529630942942,
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+ "mean_legacy_gsi": 0.21548690462276396,
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+ "mean_lift_score": 0.018565539983511955,
315
+ "mean_motion_stability_score": 0.010595505441884681
316
+ }
317
+ },
318
+ "tool": {
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+ "tool_selection_accuracy": null,
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+ "tool_switch_success_rate": null,
321
+ "tool_switch_total": 0,
322
+ "tool_switch_successful": 0
323
+ },
324
+ "runtime": {
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+ "avg_steps": 3639,
326
+ "error_count": 0
327
+ }
328
+ }
329
+ }
gpt6_astra_1x_icl/per_task_eval/76_soup_serving/Full/per_episode.jsonl ADDED
The diff for this file is too large to render. See raw diff
 
gpt6_astra_1x_icl/per_task_eval/76_soup_serving/Full/summary.json ADDED
@@ -0,0 +1,328 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "metric_schema_version": "core-v1.8-policy-step-query-split",
3
+ "metadata": {
4
+ "policy_name": "gpt-6-astra",
5
+ "base_seed": 207600000,
6
+ "seed_policy": "episode_seed = base_seed + episode_index - 1",
7
+ "randomization_recorded": true,
8
+ "n_episodes": 10,
9
+ "successes": 0,
10
+ "error_count": 0,
11
+ "evaluation_protocol": "reach_and_stop",
12
+ "early_stop": true,
13
+ "success_definition": "terminal.raw_condition holds for dwell_time_s",
14
+ "measurement_window": "episode_start_to_stable_success_or_failure_budget",
15
+ "max_episode_steps": 2958,
16
+ "dwell_time_s": 0.5,
17
+ "field_semantics": {
18
+ "success_rate": "primary protocol success rate: stable_success for reach_and_stop; terminal at_end_success_budget for fixed_horizon",
19
+ "avg_time_to_success_s": "main efficiency metric: mean time_to_stable_success_s over reached-success episodes",
20
+ "task_efficiency": "benchmark-specific expert-normalized speed ratio: expert_time_s / time_to_stable_success_s over reached-success episodes",
21
+ "avg_steps_to_success": "diagnostic mean steps_to_stable_success over reached-success episodes, or None if no episode succeeds",
22
+ "avg_policy_steps_to_success": "diagnostic mean policy-rate control/action steps through stable success over reached-success episodes",
23
+ "avg_policy_queries_to_success": "diagnostic mean actual model inference queries through stable success over reached-success episodes; None when the first-success query count was not observed",
24
+ "safe_success_rate": "episode success rate with no task-level hard safety violation (drop or tracked-object high speed; joint limits are diagnostic by default)",
25
+ "hard_violation_rate": "episode rate with any task-level hard safety violation (drop or tracked-object high speed; joint limits are diagnostic by default)",
26
+ "drop_rate": "episode rate with drop_off_table or drop_to_table_after_lift violation",
27
+ "high_speed_violation_rate": "episode rate with any tracked object exceeding the configured speed threshold",
28
+ "excessive_impact_rate": "deprecated contact-force impact metric; no longer populated by core safety",
29
+ "robot_constraint_violation_rate": "diagnostic episode rate with any asset hard-joint-limit observation; excluded from safe_success_rate unless include_in_core_safety is explicitly enabled",
30
+ "finger_joint_limit_saturation_rate": "episode rate with dexterous finger joints saturated beyond finger joint-limit thresholds; diagnostic by default and not included in safe_success_rate",
31
+ "joint_limit_active_step_rate": "diagnostic mean fraction of steps with any joint exceeding the soft diagnostic margin",
32
+ "finger_joint_limit_saturation_step_rate": "diagnostic mean fraction of steps with finger joint-limit saturation",
33
+ "max_joint_limit_excess_rad": "diagnostic maximum operating/soft-limit excess observed in radians; hard-limit source and role validation are in robot_constraint_diagnostics",
34
+ "safety_violation_rate_time": "compatibility diagnostic; with fixed physics_dt this is equivalent to safety_violation_step_rate and is omitted from grouped summary output",
35
+ "safety_violation_step_rate": "core safety metric: fraction of executed steps with task-level safety violations; joint-limit observations are excluded by default",
36
+ "safety_violation_rate_event": "deprecated compatibility alias of safety_violation_events_per_step; omitted from grouped summary output",
37
+ "safety_violation_events_per_step": "diagnostic event density; may exceed 1 when multiple violations happen in one step",
38
+ "episode_violation_rate": "compatibility alias of hard_violation_rate; omitted from grouped core output",
39
+ "latched_stage_completion_rate": "main progress metric; ever-reached stage completion rate at episode end",
40
+ "current_stage_completion_rate": "diagnostic terminal-state stage completion rate at episode end",
41
+ "current_normalized_progress_score": "chain-depth diagnostic; normalized progress score at episode end",
42
+ "current_chain_depth_progress_score": "alias of current_normalized_progress_score for ordered dependency-depth diagnostics",
43
+ "latched_chain_depth_progress_score": "alias of latched_normalized_progress_score for ever-reached dependency-depth diagnostics",
44
+ "robustness": "success rates grouped by benchmark protocol category: cov, inv, and inv+cov"
45
+ }
46
+ },
47
+ "core_metrics": {
48
+ "completion": {
49
+ "success_rate": 0.0,
50
+ "success_rate_ci": {
51
+ "mean": 0.0,
52
+ "ci_low": 0.0,
53
+ "ci_high": 0.0
54
+ }
55
+ },
56
+ "progress": {
57
+ "latched_stage_completion_rate": 0.425
58
+ },
59
+ "efficiency": {
60
+ "avg_time_to_success_s": null
61
+ },
62
+ "safety": {
63
+ "safe_success_rate": 0.0,
64
+ "hard_violation_rate": 0.9,
65
+ "drop_rate": 0.9,
66
+ "high_speed_violation_rate": 0.2,
67
+ "safety_violation_step_rate": 0.0017917511832319134
68
+ },
69
+ "robustness": {}
70
+ },
71
+ "diagnostic_metrics": {
72
+ "completion": {
73
+ "ever_instant_success_rate": 0.0,
74
+ "at_end_success_rate": 0.0,
75
+ "task_family_success_rate": {
76
+ "bimanual_soup_scoop_serve": 0.0
77
+ }
78
+ },
79
+ "progress": {
80
+ "current_stage_completion_rate": 0.375,
81
+ "current_chain_depth_progress_score": 0.5,
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+ "latched_chain_depth_progress_score": 0.5666666666666667,
83
+ "avg_current_chain_depth": 1.5,
84
+ "avg_latched_chain_depth": 1.7
85
+ },
86
+ "efficiency": {
87
+ "task_efficiency": null,
88
+ "expert_time_s": 32.86666666666667,
89
+ "expert_time_step": 1972,
90
+ "avg_steps_to_success": null,
91
+ "avg_policy_steps_to_success": null,
92
+ "avg_policy_queries_to_success": null
93
+ },
94
+ "safety": {
95
+ "safety_violation_events_per_step": 0.0006423258958755916,
96
+ "violation_counts": {
97
+ "drop_obj_330_bowl_2": 1,
98
+ "drop_to_table_obj_330_bowl_2": 8,
99
+ "drop_to_table_obj_330_ladle_3": 8,
100
+ "high_speed_distractor_00_clutter_019_pitcher_base": 1,
101
+ "high_speed_obj_330_bowl_2": 1
102
+ },
103
+ "robot_constraint_violation_rate": 1.0,
104
+ "finger_joint_limit_saturation_rate": 1.0,
105
+ "joint_limit_active_step_rate": 0.14533468559837728,
106
+ "finger_joint_limit_saturation_step_rate": 0.10256930358350237,
107
+ "max_joint_limit_excess_rad": 1.776158094406128,
108
+ "robot_constraint_diagnostics": {
109
+ "joint_limit_soft_counts": {
110
+ "FFJ1": 38,
111
+ "FFJ2": 111,
112
+ "FFJ3": 37,
113
+ "FFJ4": 4,
114
+ "LFJ2": 23,
115
+ "LFJ4": 58,
116
+ "LFJ5": 76,
117
+ "MFJ1": 1,
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+ "MFJ2": 219,
119
+ "MFJ4": 87,
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+ "RFJ2": 64,
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+ "RFJ4": 56,
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+ "THJ2": 3,
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+ "THJ3": 12,
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+ "THJ4": 229,
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+ "THJ5": 156,
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+ "WRJ1": 16,
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+ "WRJ2": 43,
128
+ "l_FFJ1": 131,
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+ "l_FFJ2": 845,
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+ "l_FFJ3": 229,
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+ "l_LFJ1": 9,
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+ "l_LFJ2": 576,
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+ "l_LFJ5": 731,
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+ "l_MFJ1": 60,
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+ "l_MFJ4": 53,
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+ "l_RFJ1": 3,
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+ "l_RFJ2": 1879,
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+ "l_RFJ3": 273,
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+ "l_RFJ4": 36,
144
+ "l_THJ4": 160,
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+ "l_THJ5": 35,
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+ "l_WRJ2": 1
147
+ },
148
+ "joint_limit_hard_counts": {
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+ "FFJ1": 1,
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+ "FFJ2": 16,
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+ "FFJ3": 3,
152
+ "FFJ4": 1,
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+ "LFJ1": 1,
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156
+ "LFJ4": 14,
157
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160
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+ "RFJ2": 13,
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+ "THJ2": 1,
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+ "THJ3": 1,
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+ "THJ4": 20,
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+ "WRJ1": 1,
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+ "WRJ2": 1,
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+ "l_FFJ1": 12,
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+ "l_FFJ2": 23,
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+ "l_FFJ3": 8,
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+ "l_LFJ1": 3,
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+ "l_LFJ2": 25,
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+ "l_THJ4": 3,
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+ "l_WRJ2": 1
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+ },
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+ "joint_limit_hard_episode_events": 181,
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+ "finger_joint_limit_saturation_counts": {
191
+ "FFJ1": 35,
192
+ "FFJ2": 15,
193
+ "FFJ3": 11,
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+ "LFJ4": 1,
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+ "MFJ4": 37,
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+ "RFJ4": 21,
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+ "THJ3": 6,
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+ "l_FFJ1": 119,
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+ "l_FFJ2": 598,
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+ "l_FFJ3": 25,
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+ "l_RFJ4": 1,
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+ "l_THJ4": 107
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+ },
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+ "joint_limit_max_excess_by_joint": {
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+ "FFJ1": 1.4879580736160278,
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+ "FFJ2": 0.43703046441078186,
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+ "FFJ3": 0.3517078161239624,
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+ "LFJ1": 0.00720801530405879,
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+ "LFJ5": 0.3535561263561249,
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+ "MFJ1": 0.0374506413936615,
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+ "MFJ2": 0.7520123720169067,
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+ "MFJ4": 0.22446885704994202,
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+ "RFJ1": 0.003974391613155603,
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+ "RFJ2": 0.17116332054138184,
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+ "RFJ4": 0.28328296542167664,
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+ "THJ2": 0.09219378232955933,
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+ "WRJ1": 0.10897630453109741,
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+ "l_FFJ1": 1.611231803894043,
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+ "l_FFJ2": 0.7768445611000061,
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+ "l_FFJ3": 0.19642049074172974,
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+ "l_LFJ4": 1.100192904472351,
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+ "l_LFJ5": 1.776158094406128,
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+ "l_MFJ1": 0.689359724521637,
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+ "l_RFJ1": 0.01248151995241642,
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+ "l_RFJ3": 0.21871352195739746,
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+ "l_RFJ4": 0.2540991008281708,
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+ "l_THJ1": 3.4332275390625e-05,
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+ "l_THJ2": 0.00016617774963378906,
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+ "l_THJ4": 0.8159288167953491,
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+ "l_THJ5": 0.056596994400024414,
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+ "l_WRJ1": 0.0025249123573303223,
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+ "l_WRJ2": 0.010103315114974976
262
+ },
263
+ "coverage": {
264
+ "hard_limit_source": {
265
+ "available": 10,
266
+ "unavailable": 0,
267
+ "unknown": 0
268
+ },
269
+ "joint_role_manifest": {
270
+ "available": 10,
271
+ "unavailable": 0,
272
+ "unknown": 0
273
+ }
274
+ },
275
+ "hard_limit_sources": {
276
+ "runtime.joint_pos_limits": 10
277
+ },
278
+ "soft_limit_sources": {
279
+ "runtime.soft_joint_pos_limits": 10
280
+ },
281
+ "unknown_runtime_joint_names": [],
282
+ "baseline_checks": {
283
+ "post_home": {
284
+ "checked": 10,
285
+ "hard_violation_episodes": 0
286
+ },
287
+ "post_reset": {
288
+ "checked": 10,
289
+ "hard_violation_episodes": 0
290
+ }
291
+ }
292
+ }
293
+ },
294
+ "robot_motion": {
295
+ "joint_acceleration_rms": 20.435814333606697,
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+ "joint_effort_rms": 46.37797538179373,
297
+ "joint_jerk_rms": 2096.443657576408,
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+ "joint_velocity_rms": 0.39872399002143477
299
+ },
300
+ "grasp": {
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+ "kinematic_grasp_stability_index": 0.9920605397375284,
302
+ "mean_kinematic_grasp_stability": 0.6440057063325317,
303
+ "per_object_best_kinematic_grasp_stability": {
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+ "obj_330_bowl_2": 0.9647714908991828,
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+ "obj_330_ladle_3": 0.9608106828040366
306
+ },
307
+ "grasp_gsi_diagnostics": {
308
+ "mean_anti_slip_score": 0.7896777101645251,
309
+ "mean_duration_score": 0.7264153707459993,
310
+ "mean_hold_score": 0.4236384381338793,
311
+ "mean_kinematic_stability_score": 0.2652297121587954,
312
+ "mean_legacy_gsi": 0.5461500173370503,
313
+ "mean_lift_score": 0.5291075050709939,
314
+ "mean_motion_stability_score": 0.37767901349760563
315
+ }
316
+ },
317
+ "tool": {
318
+ "tool_selection_accuracy": null,
319
+ "tool_switch_success_rate": null,
320
+ "tool_switch_total": 0,
321
+ "tool_switch_successful": 0
322
+ },
323
+ "runtime": {
324
+ "avg_steps": 2958,
325
+ "error_count": 0
326
+ }
327
+ }
328
+ }