Show measured efficiency values with incomplete coverage markers

README.md

@@ -2224,11 +2224,11 @@ Confidence intervals use 10,000 asset-cluster bootstrap samples, retaining the f
 
 ### Efficiency
 
-Efficiency is the mean fidelity divided by mean resource use per eligible reconstruction. Token efficiency uses total input and output tokens, while time efficiency uses elapsed reconstruction time, including model requests, tools and evaluation. Each ratio uses the same eligible reconstructions for its score and resource means, with joint asset-cluster bootstrap intervals.
+Efficiency is the mean fidelity divided by mean resource use across eligible reconstructions with both measurements. Token efficiency uses total input and output tokens, while time efficiency uses elapsed reconstruction time, including model requests, tools and evaluation. Cost efficiency uses pricing-derived inference cost in USD, with compute cost reported separately. Each ratio uses paired score and resource measurements, with joint asset-cluster bootstrap intervals.
 
 | Configuration | Formal points/1M tokens | Visual points/1M tokens | Kinematic points/1M tokens |
 | --- | ---: | ---: | ---: |
-| gpt-6.1-sol<br>high reasoning, pi, skills: none<br>authoring-64-native-output-v1 | unknown (97/100 measured) | unknown (97/100 measured) | unknown (54/55 measured) |
+| gpt-6.1-sol<br>high reasoning, pi, skills: none<br>authoring-64-native-output-v1 | 102.90 [95.98, 110.80]* | 46.34 [37.17, 55.88]* | 6.83 [0.25, 19.09]* |
 
 ![Formal, visual and kinematic fidelity points per million tokens with 95% confidence intervals.](media/leaderboard-token-efficiency.png)
 
@@ -2238,13 +2238,21 @@ Efficiency is the mean fidelity divided by mean resource use per eligible recons
 
 ![Formal, visual and kinematic fidelity points per elapsed minute with 95% confidence intervals.](media/leaderboard-time-efficiency.png)
 
+| Configuration | Formal points/USD inference | Visual points/USD inference | Kinematic points/USD inference |
+| --- | ---: | ---: | ---: |
+| gpt-6.1-sol<br>high reasoning, pi, skills: none<br>authoring-64-native-output-v1 | 219.61 [204.88, 234.78]* | 98.90 [79.01, 118.91]* | 14.48 [0.51, 41.55]* |
+
+![Formal, visual and kinematic fidelity points per USD of pricing-derived inference cost with 95% confidence intervals.](media/leaderboard-inference-cost-efficiency.png)
+
 ### Resource use
 
-Means per reconstruction across all 100 attempts. Partial measurement coverage is shown in place of a mean. Full precision and eligible-attempt coverage are retained in [leaderboard.json](leaderboard.json).
+Means per reconstruction with measured usage. Full precision, totals and measurement coverage are retained in [leaderboard.json](leaderboard.json).
+
+| Configuration | Total tokens | Elapsed minutes | Model requests | Pricing-derived inference cost (USD) | Compute cost (USD) | Total cost (USD) |
+| --- | ---: | ---: | ---: | ---: | ---: | ---: |
+| gpt-6.1-sol<br>high reasoning, pi, skills: none<br>authoring-64-native-output-v1 | 971,775.96* | 10.31 | 36.02 | 0.46* | unknown | unknown |
 
-| Configuration | Total tokens | Elapsed minutes | Model requests | Cost (USD) |
-| --- | ---: | ---: | ---: | ---: |
-| gpt-6.1-sol<br>high reasoning, pi, skills: none<br>authoring-64-native-output-v1 | unknown (97/100 measured) | 10.31 | 36.02 | unknown (0/100 measured) |
+\* Incomplete usage coverage.
 
 ### Strict conformance
 

leaderboard.json

@@ -1,433 +1,541 @@
-{
-  "schema": "simreadybench-leaderboard/v1",
-  "entries": [
-    {
-      "reference_set": "NV25",
-      "reference_revision": "f4860aa0c75607adb50a78bf96e77510bffc040f",
-      "benchmark_freeze": {
-        "id": "nvidia-25",
-        "version": "1"
-      },
-      "reference_count": 25,
-      "repetitions": 4,
-      "completed_attempts": 100,
-      "model": "gpt-6.1-sol",
-      "harness": "pi",
-      "reasoning_effort": "high",
-      "authoring_protocol": "authoring-64-native-output-v1",
-      "inference_requests_per_attempt": 64,
-      "skills": [],
-      "compliance": 100.0,
-      "usage": {
-        "inference_calls_used": {
-          "mean": 36.02,
-          "measured_attempts": 100,
-          "total_attempts": 100
-        },
-        "validation_calls_used": {
-          "mean": 3.01,
-          "measured_attempts": 100,
-          "total_attempts": 100
-        },
-        "model_request_errors": {
-          "mean": 0,
-          "measured_attempts": 100,
-          "total_attempts": 100
-        },
-        "elapsed_seconds": {
-          "mean": 618.5340745433548,
-          "measured_attempts": 100,
-          "total_attempts": 100
-        },
-        "model_request_seconds": {
-          "mean": 523.1639625989552,
-          "measured_attempts": 100,
-          "total_attempts": 100
-        },
-        "input_tokens": {
-          "mean": null,
-          "measured_attempts": 97,
-          "total_attempts": 100
-        },
-        "output_tokens": {
-          "mean": null,
-          "measured_attempts": 97,
-          "total_attempts": 100
-        },
-        "total_tokens": {
-          "mean": null,
-          "measured_attempts": 97,
-          "total_attempts": 100
-        },
-        "inference_cost_usd": {
-          "mean": null,
-          "measured_attempts": 97,
-          "total_attempts": 100
-        },
-        "compute_cost_usd": {
-          "mean": null,
-          "measured_attempts": 0,
-          "total_attempts": 100
-        },
-        "total_cost_usd": {
-          "mean": null,
-          "measured_attempts": 0,
-          "total_attempts": 100
-        }
-      },
-      "mandatory": {
-        "score": 100.0,
-        "passed": 4600,
-        "failed": 0,
-        "unknown": 0,
-        "eligible": 4600,
-        "measured": 4600,
-        "coverage": 100.0,
-        "lower_bound": 100.0,
-        "upper_bound": 100.0,
-        "measured_attempts": 100,
-        "unknown_attempts": 0,
-        "reported_attempts": 100,
-        "completion_bonus": 5
-      },
-      "optional": {
-        "score": 73.7843137254902,
-        "passed": 3763,
-        "failed": 1337,
-        "unknown": 0,
-        "eligible": 5100,
-        "measured": 5100,
-        "coverage": 100.0,
-        "lower_bound": 73.7843137254902,
-        "upper_bound": 73.7843137254902,
-        "measured_attempts": 100,
-        "unknown_attempts": 0,
-        "reported_attempts": 100,
-        "confidence_interval": {
-          "level": 0.95,
-          "lower": 72.96078431372548,
-          "upper": 74.56862745098039,
-          "method": "asset_cluster_bootstrap_percentile",
-          "resamples": 10000,
-          "seed": 20261020,
-          "asset_count": 25
-        },
-        "eligible_assets": 25
-      },
-      "fidelity": {
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-          "status": "measured",
-          "earned": 75.53614146601535,
-          "eligible": 100,
-          "measured": 100,
-          "coverage": 100.0,
-          "measurement_coverage": 100.0,
-          "eligible_attempts": 100,
-          "measured_attempts": 100,
-          "not_applicable_attempts": 0,
-          "unknown_eligibility_attempts": 0,
-          "unknown_attempts": 0,
-          "lower_bound": 75.53614146601535,
-          "upper_bound": 75.53614146601535
-        },
-        "rigid_parts": {
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-          "status": "measured",
-          "earned": 113.87152565910199,
-          "eligible": 228,
-          "measured": 228,
-          "coverage": 100.0,
-          "measurement_coverage": 100.0,
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-          "measured_attempts": 100,
-          "not_applicable_attempts": 0,
-          "unknown_eligibility_attempts": 0,
-          "unknown_attempts": 0,
-          "lower_bound": 59.5209952816981,
-          "upper_bound": 59.5209952816981
-        },
-        "joints": {
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-          "status": "measured",
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-          "measured": 1288,
-          "coverage": 100.0,
-          "measurement_coverage": 100.0,
-          "eligible_attempts": 40,
-          "measured_attempts": 40,
-          "not_applicable_attempts": 60,
-          "unknown_eligibility_attempts": 0,
-          "unknown_attempts": 0,
-          "lower_bound": 53.907993286084135,
-          "upper_bound": 53.907993286084135
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-        "materials": {
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-          "measurement_coverage": 100.0,
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-          "measured_attempts": 100,
-          "not_applicable_attempts": 0,
-          "unknown_eligibility_attempts": 0,
-          "unknown_attempts": 0,
-          "lower_bound": 30.40401221317391,
-          "upper_bound": 30.40401221317391
-        }
-      },
-      "composite_scores": {
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-          "status": "measured",
-          "earned": 4600,
-          "eligible": 4600,
-          "measured": 4600,
-          "coverage": 100.0,
-          "measurement_coverage": 100.0,
-          "eligible_attempts": 100,
-          "measured_attempts": 100,
-          "not_applicable_attempts": 0,
-          "unknown_eligibility_attempts": 0,
-          "unknown_attempts": 0,
-          "lower_bound": 100.0,
-          "upper_bound": 100.0,
-          "confidence_interval": {
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-            "lower": 100.0,
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-            "method": "asset_cluster_bootstrap_percentile",
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-          "coverage": 100.0,
-          "measurement_coverage": 100.0,
-          "eligible_attempts": 100,
-          "measured_attempts": 100,
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-          "unknown_attempts": 0,
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-            "method": "asset_cluster_bootstrap_percentile",
-            "resamples": 10000,
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-          },
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-        "kinematic": {
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-          "status": "measured",
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-          "eligible": 75,
-          "measured": 75,
-          "coverage": 100.0,
-          "measurement_coverage": 100.0,
-          "eligible_attempts": 55,
-          "measured_attempts": 55,
-          "not_applicable_attempts": 45,
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-            "method": "asset_cluster_bootstrap_percentile",
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-            "seed": 20261020,
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-          },
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-        }
-      },
-      "efficiency": {
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-            "status": "unknown",
-            "unit": "fidelity points per million tokens",
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-            "eligible_attempts": 100,
-            "eligible_assets": 25,
-            "total_attempts": 100,
-            "denominator": "mean_total_tokens_per_eligible_attempt",
-            "denominator_mean": null,
-            "multiplier": 1000000
-          },
-          "per_elapsed_minute": {
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-              "method": "asset_cluster_bootstrap_percentile",
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-              "seed": 20261020,
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-        },
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-        "kinematic": {
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-            "unit": "fidelity points per million tokens",
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-      "success": {
-        "mandatory_pass_per_attempt": {
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-          "passed": 100,
-          "measured": 100,
-          "total": 100
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-        "mandatory_pass_within_four": {
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-          "passed": 25,
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-        }
-      },
-      "profile": {
-        "id": "Robotics-Prop",
-        "version": "4.0.0"
-      },
-      "results_url": "https://huggingface.co/datasets/hcltech-robotics/simreadybench/blob/main/runs/nv25-gpt-6.1-sol-high-pi-none-turn64-20261020/report.html"
-    }
-  ]
-}
+{
+  "schema": "simreadybench-leaderboard/v1",
+  "entries": [
+    {
+      "reference_set": "NV25",
+      "reference_revision": "f4860aa0c75607adb50a78bf96e77510bffc040f",
+      "benchmark_freeze": {
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+        "version": "1"
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+      "repetitions": 4,
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+      "model": "gpt-6.1-sol",
+      "harness": "pi",
+      "reasoning_effort": "high",
+      "authoring_protocol": "authoring-64-native-output-v1",
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+      "skills": [],
+      "compliance": 100.0,
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+        "coverage": 100.0,
+        "lower_bound": 73.7843137254902,
+        "upper_bound": 73.7843137254902,
+        "measured_attempts": 100,
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+        "confidence_interval": {
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+          "lower": 72.96078431372548,
+          "upper": 74.56862745098039,
+          "method": "asset_cluster_bootstrap_percentile",
+          "resamples": 10000,
+          "seed": 20261020,
+          "asset_count": 25
+        },
+        "eligible_assets": 25
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+      "fidelity": {
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+          "eligible": 100,
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+        "rigid_parts": {
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+      "success": {
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+      "profile": {
+        "id": "Robotics-Prop",
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+      "results_url": "https://huggingface.co/datasets/hcltech-robotics/simreadybench/blob/main/runs/nv25-gpt-6.1-sol-high-pi-none-turn64-20261020/report.html"
+    }
+  ]
+}

viewer-index.json

@@ -1,471 +1,471 @@
-{
-  "schema": "simreadybench-viewer-index/v3",
-  "runs": {
-    "fresh-v1-nv25-gpt-6.1-sol-pi-none-medium-turn64-20261020": {
-      "scores": "runs/fresh-v1-nv25-gpt-6.1-sol-pi-none-medium-turn64-20261020/scores.csv",
-      "viewer_scores": "viewer/fresh-v1-nv25-gpt-6.1-sol-pi-none-medium-turn64-20261020/scores.parquet",
-      "groups": {
-        "by_model": [
-          {
-            "split": "gpt_6_1_sol",
-            "path": "viewer/fresh-v1-nv25-gpt-6.1-sol-pi-none-medium-turn64-20261020/scores.parquet"
-          }
-        ],
-        "by_harness": [
-          {
-            "split": "pi",
-            "path": "viewer/fresh-v1-nv25-gpt-6.1-sol-pi-none-medium-turn64-20261020/scores.parquet"
-          }
-        ],
-        "by_skills": [
-          {
-            "split": "none",
-            "path": "viewer/fresh-v1-nv25-gpt-6.1-sol-pi-none-medium-turn64-20261020/scores.parquet"
-          }
-        ],
-        "by_reference_set": [
-          {
-            "split": "nv25",
-            "path": "viewer/fresh-v1-nv25-gpt-6.1-sol-pi-none-medium-turn64-20261020/scores.parquet"
-          }
-        ],
-        "by_protocol": [
-          {
-            "split": "authoring_64_native_output_v1",
-            "path": "viewer/fresh-v1-nv25-gpt-6.1-sol-pi-none-medium-turn64-20261020/scores.parquet"
-          }
-        ],
-        "by_reasoning": [
-          {
-            "split": "unknown",
-            "path": "viewer/fresh-v1-nv25-gpt-6.1-sol-pi-none-medium-turn64-20261020/scores.parquet"
-          }
-        ],
-        "by_asset": [
-          {
-            "split": "accessory_eyeglasses_a01",
-            "path": "viewer/fresh-v1-nv25-gpt-6.1-sol-pi-none-medium-turn64-20261020/by_asset/accessory_eyeglasses_a01.parquet"
-          },
-          {
-            "split": "box_cardboard_open_a01",
-            "path": "viewer/fresh-v1-nv25-gpt-6.1-sol-pi-none-medium-turn64-20261020/by_asset/box_cardboard_open_a01.parquet"
-          },
-          {
-            "split": "bucket_utility_red_a01",
-            "path": "viewer/fresh-v1-nv25-gpt-6.1-sol-pi-none-medium-turn64-20261020/by_asset/bucket_utility_red_a01.parquet"
-          },
-          {
-            "split": "chair_office_amf_black_a01",
-            "path": "viewer/fresh-v1-nv25-gpt-6.1-sol-pi-none-medium-turn64-20261020/by_asset/chair_office_amf_black_a01.parquet"
-          }
-        ]
-      }
-    },
-    "nv25-gpt-6.1-sol-high-pi-none-turn64-20261020": {
-      "scores": "runs/nv25-gpt-6.1-sol-high-pi-none-turn64-20261020/scores.csv",
-      "viewer_scores": "viewer/nv25-gpt-6.1-sol-high-pi-none-turn64-20261020/scores.parquet",
-      "groups": {
-        "by_model": [
-          {
-            "split": "gpt_6_1_sol",
-            "path": "viewer/nv25-gpt-6.1-sol-high-pi-none-turn64-20261020/scores.parquet"
-          }
-        ],
-        "by_harness": [
-          {
-            "split": "pi",
-            "path": "viewer/nv25-gpt-6.1-sol-high-pi-none-turn64-20261020/scores.parquet"
-          }
-        ],
-        "by_skills": [
-          {
-            "split": "none",
-            "path": "viewer/nv25-gpt-6.1-sol-high-pi-none-turn64-20261020/scores.parquet"
-          }
-        ],
-        "by_reference_set": [
-          {
-            "split": "nv25",
-            "path": "viewer/nv25-gpt-6.1-sol-high-pi-none-turn64-20261020/scores.parquet"
-          }
-        ],
-        "by_protocol": [
-          {
-            "split": "authoring_64_native_output_v1",
-            "path": "viewer/nv25-gpt-6.1-sol-high-pi-none-turn64-20261020/scores.parquet"
-          }
-        ],
-        "by_reasoning": [
-          {
-            "split": "high",
-            "path": "viewer/nv25-gpt-6.1-sol-high-pi-none-turn64-20261020/scores.parquet"
-          }
-        ],
-        "by_asset": [
-          {
-            "split": "accessory_eyeglasses_a01",
-            "path": "viewer/nv25-gpt-6.1-sol-high-pi-none-turn64-20261020/by_asset/accessory_eyeglasses_a01.parquet"
-          },
-          {
-            "split": "box_cardboard_open_a01",
-            "path": "viewer/nv25-gpt-6.1-sol-high-pi-none-turn64-20261020/by_asset/box_cardboard_open_a01.parquet"
-          },
-          {
-            "split": "bucket_utility_red_a01",
-            "path": "viewer/nv25-gpt-6.1-sol-high-pi-none-turn64-20261020/by_asset/bucket_utility_red_a01.parquet"
-          },
-          {
-            "split": "chair_office_amf_black_a01",
-            "path": "viewer/nv25-gpt-6.1-sol-high-pi-none-turn64-20261020/by_asset/chair_office_amf_black_a01.parquet"
-          },
-          {
-            "split": "cleaning_cloth_a01",
-            "path": "viewer/nv25-gpt-6.1-sol-high-pi-none-turn64-20261020/by_asset/cleaning_cloth_a01.parquet"
-          },
-          {
-            "split": "container_bottle_glass_a01",
-            "path": "viewer/nv25-gpt-6.1-sol-high-pi-none-turn64-20261020/by_asset/container_bottle_glass_a01.parquet"
-          },
-          {
-            "split": "enginecomponent_camshaft_a01",
-            "path": "viewer/nv25-gpt-6.1-sol-high-pi-none-turn64-20261020/by_asset/enginecomponent_camshaft_a01.parquet"
-          },
-          {
-            "split": "food_beverage_coffeecup_a01",
-            "path": "viewer/nv25-gpt-6.1-sol-high-pi-none-turn64-20261020/by_asset/food_beverage_coffeecup_a01.parquet"
-          },
-          {
-            "split": "food_prepared_croissant_a01",
-            "path": "viewer/nv25-gpt-6.1-sol-high-pi-none-turn64-20261020/by_asset/food_prepared_croissant_a01.parquet"
-          },
-          {
-            "split": "food_produce_banana_a01",
-            "path": "viewer/nv25-gpt-6.1-sol-high-pi-none-turn64-20261020/by_asset/food_produce_banana_a01.parquet"
-          },
-          {
-            "split": "food_produce_broccoli_b01",
-            "path": "viewer/nv25-gpt-6.1-sol-high-pi-none-turn64-20261020/by_asset/food_produce_broccoli_b01.parquet"
-          },
-          {
-            "split": "handtool_hammer_crosspeen_a01",
-            "path": "viewer/nv25-gpt-6.1-sol-high-pi-none-turn64-20261020/by_asset/handtool_hammer_crosspeen_a01.parquet"
-          },
-          {
-            "split": "handtool_wrench_adjustable_a01",
-            "path": "viewer/nv25-gpt-6.1-sol-high-pi-none-turn64-20261020/by_asset/handtool_wrench_adjustable_a01.parquet"
-          },
-          {
-            "split": "handtruck_convertible_steel_red_a01",
-            "path": "viewer/nv25-gpt-6.1-sol-high-pi-none-turn64-20261020/by_asset/handtruck_convertible_steel_red_a01.parquet"
-          },
-          {
-            "split": "kitchenware_kettle_a01",
-            "path": "viewer/nv25-gpt-6.1-sol-high-pi-none-turn64-20261020/by_asset/kitchenware_kettle_a01.parquet"
-          },
-          {
-            "split": "kitchenware_pan_j01",
-            "path": "viewer/nv25-gpt-6.1-sol-high-pi-none-turn64-20261020/by_asset/kitchenware_pan_j01.parquet"
-          },
-          {
-            "split": "pallet_wood_recycled_a05",
-            "path": "viewer/nv25-gpt-6.1-sol-high-pi-none-turn64-20261020/by_asset/pallet_wood_recycled_a05.parquet"
-          },
-          {
-            "split": "powertool_drill_b01",
-            "path": "viewer/nv25-gpt-6.1-sol-high-pi-none-turn64-20261020/by_asset/powertool_drill_b01.parquet"
-          },
-          {
-            "split": "ppe_helmet_hardhat_a01",
-            "path": "viewer/nv25-gpt-6.1-sol-high-pi-none-turn64-20261020/by_asset/ppe_helmet_hardhat_a01.parquet"
-          },
-          {
-            "split": "servicetool_funnel_flexiblespout_a01",
-            "path": "viewer/nv25-gpt-6.1-sol-high-pi-none-turn64-20261020/by_asset/servicetool_funnel_flexiblespout_a01.parquet"
-          },
-          {
-            "split": "sign_wetfloor_a01",
-            "path": "viewer/nv25-gpt-6.1-sol-high-pi-none-turn64-20261020/by_asset/sign_wetfloor_a01.parquet"
-          },
-          {
-            "split": "suspension_coilover_rear_b01",
-            "path": "viewer/nv25-gpt-6.1-sol-high-pi-none-turn64-20261020/by_asset/suspension_coilover_rear_b01.parquet"
-          },
-          {
-            "split": "tools_fireextinguisher_co2_a01",
-            "path": "viewer/nv25-gpt-6.1-sol-high-pi-none-turn64-20261020/by_asset/tools_fireextinguisher_co2_a01.parquet"
-          },
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+            "path": "viewer/nv25-gpt-6.1-sol-high-pi-none-turn64-20261020/by_asset/wheelassembly_wheel_rim_a01.parquet"
+          }
+        ]
+      }
+    },
+    "nv25-qwen38-27b-xhigh-pi-none-turn64-20261021": {
+      "scores": "runs/nv25-qwen38-27b-xhigh-pi-none-turn64-20261021/scores.csv",
+      "viewer_scores": "viewer/nv25-qwen38-27b-xhigh-pi-none-turn64-20261021/scores.parquet",
+      "groups": {
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+            "split": "qwen_qwen3_8_27b_deepinfra",
+            "path": "viewer/nv25-qwen38-27b-xhigh-pi-none-turn64-20261021/scores.parquet"
+          }
+        ],
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+            "path": "viewer/nv25-qwen38-27b-xhigh-pi-none-turn64-20261021/scores.parquet"
+          }
+        ],
+        "by_skills": [
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+            "split": "none",
+            "path": "viewer/nv25-qwen38-27b-xhigh-pi-none-turn64-20261021/scores.parquet"
+          }
+        ],
+        "by_reference_set": [
+          {
+            "split": "nv25",
+            "path": "viewer/nv25-qwen38-27b-xhigh-pi-none-turn64-20261021/scores.parquet"
+          }
+        ],
+        "by_protocol": [
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+            "split": "authoring_64_native_output_v1",
+            "path": "viewer/nv25-qwen38-27b-xhigh-pi-none-turn64-20261021/scores.parquet"
+          }
+        ],
+        "by_reasoning": [
+          {
+            "split": "xhigh",
+            "path": "viewer/nv25-qwen38-27b-xhigh-pi-none-turn64-20261021/scores.parquet"
+          }
+        ],
+        "by_asset": [
+          {
+            "split": "chair_office_amf_black_a01",
+            "path": "viewer/nv25-qwen38-27b-xhigh-pi-none-turn64-20261021/by_asset/chair_office_amf_black_a01.parquet"
+          },
+          {
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+            "path": "viewer/nv25-qwen38-27b-xhigh-pi-none-turn64-20261021/by_asset/cleaning_cloth_a01.parquet"
+          },
+          {
+            "split": "food_beverage_coffeecup_a01",
+            "path": "viewer/nv25-qwen38-27b-xhigh-pi-none-turn64-20261021/by_asset/food_beverage_coffeecup_a01.parquet"
+          },
+          {
+            "split": "food_prepared_croissant_a01",
+            "path": "viewer/nv25-qwen38-27b-xhigh-pi-none-turn64-20261021/by_asset/food_prepared_croissant_a01.parquet"
+          },
+          {
+            "split": "food_produce_banana_a01",
+            "path": "viewer/nv25-qwen38-27b-xhigh-pi-none-turn64-20261021/by_asset/food_produce_banana_a01.parquet"
+          },
+          {
+            "split": "food_produce_broccoli_b01",
+            "path": "viewer/nv25-qwen38-27b-xhigh-pi-none-turn64-20261021/by_asset/food_produce_broccoli_b01.parquet"
+          },
+          {
+            "split": "handtool_hammer_crosspeen_a01",
+            "path": "viewer/nv25-qwen38-27b-xhigh-pi-none-turn64-20261021/by_asset/handtool_hammer_crosspeen_a01.parquet"
+          },
+          {
+            "split": "servicetool_funnel_flexiblespout_a01",
+            "path": "viewer/nv25-qwen38-27b-xhigh-pi-none-turn64-20261021/by_asset/servicetool_funnel_flexiblespout_a01.parquet"
+          },
+          {
+            "split": "tools_fireextinguisher_co2_a01",
+            "path": "viewer/nv25-qwen38-27b-xhigh-pi-none-turn64-20261021/by_asset/tools_fireextinguisher_co2_a01.parquet"
+          },
+          {
+            "split": "wheelassembly_wheel_rim_a01",
+            "path": "viewer/nv25-qwen38-27b-xhigh-pi-none-turn64-20261021/by_asset/wheelassembly_wheel_rim_a01.parquet"
+          }
+        ]
+      }
+    }
+  },
+  "splits": {
+    "by_asset": {
+      "\"accessory_eyeglasses_a01\"": "accessory_eyeglasses_a01",
+      "\"box_cardboard_open_a01\"": "box_cardboard_open_a01",
+      "\"bucket_utility_red_a01\"": "bucket_utility_red_a01",
+      "\"chair_office_amf_black_a01\"": "chair_office_amf_black_a01",
+      "\"container_bottle_glass_a01\"": "container_bottle_glass_a01",
+      "\"food_beverage_coffeeCup_a01\"": "food_beverage_coffeecup_a01",
+      "\"engineComponent_camshaft_a01\"": "enginecomponent_camshaft_a01",
+      "\"cleaning_cloth_a01\"": "cleaning_cloth_a01",
+      "\"handTruck_convertible_steel_red_a01\"": "handtruck_convertible_steel_red_a01",
+      "\"kitchenware_kettle_a01\"": "kitchenware_kettle_a01",
+      "\"food_produce_broccoli_b01\"": "food_produce_broccoli_b01",
+      "\"handTool_hammer_crossPeen_a01\"": "handtool_hammer_crosspeen_a01",
+      "\"handTool_wrench_adjustable_a01\"": "handtool_wrench_adjustable_a01",
+      "\"suspension_coilover_rear_b01\"": "suspension_coilover_rear_b01",
+      "\"ppe_helmet_hardHat_a01\"": "ppe_helmet_hardhat_a01",
+      "\"serviceTool_funnel_flexibleSpout_a01\"": "servicetool_funnel_flexiblespout_a01",
+      "\"kitchenware_pan_j01\"": "kitchenware_pan_j01",
+      "\"pallet_wood_recycled_a05\"": "pallet_wood_recycled_a05",
+      "\"food_prepared_croissant_a01\"": "food_prepared_croissant_a01",
+      "\"food_produce_banana_a01\"": "food_produce_banana_a01",
+      "\"sign_wetFloor_a01\"": "sign_wetfloor_a01",
+      "\"tools_fireExtinguisher_CO2_a01\"": "tools_fireextinguisher_co2_a01",
+      "\"utensils_scissors_a01\"": "utensils_scissors_a01",
+      "\"wheelAssembly_wheel_rim_a01\"": "wheelassembly_wheel_rim_a01",
+      "\"powerTool_drill_b01\"": "powertool_drill_b01"
+    },
+    "by_harness": {
+      "\"pi\"": "pi"
+    },
+    "by_model": {
+      "\"gpt-6.1-sol\"": "gpt_6_1_sol",
+      "\"Qwen/Qwen3.8-27B:deepinfra\"": "qwen_qwen3_8_27b_deepinfra"
+    },
+    "by_protocol": {
+      "\"authoring-64-native-output-v1\"": "authoring_64_native_output_v1"
+    },
+    "by_reasoning": {
+      "null": "unknown",
+      "\"high\"": "high",
+      "\"xhigh\"": "xhigh"
+    },
+    "by_reference_set": {
+      "\"nv25\"": "nv25"
+    },
+    "by_skills": {
+      "\"none\"": "none"
+    }
+  },
+  "columns": [
+    "reference_image",
+    "candidate_image",
+    "capture_view",
+    "condition_id",
+    "asset_id",
+    "requested_model",
+    "harness_id",
+    "skill_set_id",
+    "repetition",
+    "status",
+    "formal_fidelity_percent",
+    "visual_fidelity_percent",
+    "kinematic_fidelity_percent",
+    "simready_reward",
+    "mandatory_passed",
+    "mandatory_total",
+    "mandatory_failed",
+    "mandatory_unknown",
+    "mandatory_lower_bound_percent",
+    "mandatory_upper_bound_percent",
+    "completion_bonus",
+    "optional_score_percent",
+    "optional_passed",
+    "optional_failed",
+    "optional_unknown",
+    "optional_total",
+    "optional_measured",
+    "optional_coverage",
+    "optional_lower_bound_percent",
+    "optional_upper_bound_percent",
+    "fidelity_shape_percent",
+    "fidelity_rigid_parts_percent",
+    "fidelity_joints_percent",
+    "fidelity_materials_percent",
+    "fidelity_shape_coverage",
+    "fidelity_rigid_parts_coverage",
+    "fidelity_joints_coverage",
+    "fidelity_materials_coverage",
+    "fidelity_reference_geometry_status",
+    "formal_fidelity_status",
+    "formal_fidelity_earned",
+    "formal_fidelity_eligible",
+    "formal_fidelity_measured",
+    "formal_fidelity_coverage",
+    "formal_fidelity_lower_bound_percent",
+    "formal_fidelity_upper_bound_percent",
+    "visual_fidelity_status",
+    "visual_fidelity_earned",
+    "visual_fidelity_eligible",
+    "visual_fidelity_measured",
+    "visual_fidelity_coverage",
+    "visual_fidelity_lower_bound_percent",
+    "visual_fidelity_upper_bound_percent",
+    "kinematic_fidelity_status",
+    "kinematic_fidelity_earned",
+    "kinematic_fidelity_eligible",
+    "kinematic_fidelity_measured",
+    "kinematic_fidelity_coverage",
+    "kinematic_fidelity_lower_bound_percent",
+    "kinematic_fidelity_upper_bound_percent",
+    "visual_appearance_percent",
+    "visual_appearance_status",
+    "visual_appearance_earned",
+    "visual_appearance_eligible",
+    "visual_appearance_measured",
+    "visual_appearance_coverage",
+    "visual_appearance_lower_bound_percent",
+    "visual_appearance_upper_bound_percent",
+    "kinematic_reference_joint_count",
+    "kinematic_candidate_joint_count",
+    "kinematic_matched_joint_count",
+    "kinematic_missing_joint_count",
+    "kinematic_extra_joint_count",
+    "kinematic_moving_joints_percent",
+    "kinematic_moving_joints_status",
+    "kinematic_moving_joints_earned",
+    "kinematic_moving_joints_eligible",
+    "kinematic_moving_joints_measured",
+    "kinematic_moving_joints_coverage",
+    "kinematic_moving_joints_lower_bound_percent",
+    "kinematic_moving_joints_upper_bound_percent",
+    "kinematic_fixed_constraints_percent",
+    "kinematic_fixed_constraints_status",
+    "kinematic_fixed_constraints_earned",
+    "kinematic_fixed_constraints_eligible",
+    "kinematic_fixed_constraints_measured",
+    "kinematic_fixed_constraints_coverage",
+    "kinematic_fixed_constraints_lower_bound_percent",
+    "kinematic_fixed_constraints_upper_bound_percent",
+    "fidelity_shape_earned",
+    "fidelity_shape_eligible",
+    "fidelity_shape_measured",
+    "fidelity_shape_status",
+    "fidelity_rigid_parts_earned",
+    "fidelity_rigid_parts_eligible",
+    "fidelity_rigid_parts_measured",
+    "fidelity_rigid_parts_status",
+    "fidelity_joints_earned",
+    "fidelity_joints_eligible",
+    "fidelity_joints_measured",
+    "fidelity_joints_status",
+    "fidelity_materials_earned",
+    "fidelity_materials_eligible",
+    "fidelity_materials_measured",
+    "fidelity_materials_status",
+    "fidelity_shape_precision",
+    "fidelity_shape_recall",
+    "fidelity_shape_samples_each_direction",
+    "fidelity_rigid_parts_geometry_percent",
+    "fidelity_rigid_parts_structure_percent",
+    "fidelity_rigid_parts_structure_earned",
+    "fidelity_rigid_parts_structure_eligible",
+    "fidelity_joints_reference_count",
+    "fidelity_joints_candidate_count",
+    "inference_calls_used",
+    "validation_calls_used",
+    "model_request_errors",
+    "elapsed_seconds",
+    "model_request_seconds",
+    "input_tokens",
+    "output_tokens",
+    "total_tokens",
+    "inference_cost_usd",
+    "compute_cost_usd",
+    "total_cost_usd"
+  ],
+  "schema_sha256": "6f9ec2e7dc82991951c6003396d5b770fdd1197fbb63e4ced39ff45996488f56"
+}