{
 "title": "Round 4: a second judge family over the whole corpus",
 "generated_by": "analyze_round4_second_judge.py",
 "read_this_first": "Two judge families scored every craft session: Claude Sonnet 5 (the published tier) and ChatGPT via Codex (subscription, blind). The letter stays Sonnet's. This file says how far the two agree, how much of their gap is one scale offset, which models' letters depend on the judge, and what vendor-linked differences remain. It does not say which judge is right.",
 "judges": {
  "first": {
   "judge": "subagent-sonnet-5",
   "label": "Claude Sonnet 5 (session judge v2)",
   "role": "sets the published letter",
   "file": "session_judge_v2.jsonl",
   "rows": {
    "rows": 1328,
    "hashed": 549,
    "unhashed_single_transcript": 779,
    "transcripts_without_a_row": 0
   }
  },
  "second": {
   "judge": "chatgpt",
   "label": "ChatGPT via Codex (subscription, blind)",
   "package": "results/judge_full_chatgpt/merged",
   "harness": "ChatGPT run blind in Codex on a ChatGPT subscription: opaque ids, no model or seed names; 1149 sessions in eleven chunks of about 100. One coordinating session, as Levi asked, gave each whole chunk to its own clean-context agent, three at a time, not one conversation per chunk as the package planned (the judges' reports: judge_full_chatgpt/app_pass/reports). The other 179 rows are reused from the earlier blind ChatGPT passes (judge_round2_chatgpt, judge_inc1_chatgpt) on byte-identical text; each of those was also a coordinator handing parts to three clean-context raters (their METHOD.md), and where they ran is not recorded",
   "model_version": "not recorded by Codex",
   "rows_by_source": {
    "judge_full_chatgpt/app_pass": 1149,
    "judge_inc1_chatgpt/external_blind_pass": 84,
    "judge_round2_chatgpt/external_blind_pass": 95
   },
   "files": [
    "external_part_app.json",
    "external_part_reused_inc1_chatgpt.json",
    "external_part_reused_round2_chatgpt.json"
   ],
   "stale_dropped": 0,
   "unmatched_dropped": 0
  }
 },
 "coverage": {
  "corpus_sessions": 1328,
  "sessions_with_both": 1328,
  "models": 70,
  "tiered_models": 69,
  "untiered": [
   {
    "model": "mistral_small_2603",
    "n_seeds": 4,
    "sessions": 4
   }
  ],
  "twelve_seed_models": [
   "claude_opus_4_7",
   "deepseek_v4_flash",
   "deepseek_v4_pro",
   "gemini_3_1_flash_lite",
   "gemini_3_1_pro",
   "glm_5_1",
   "kimi_k2_5"
  ],
  "seeds": 20,
  "bridge_sessions": 24,
  "note": "Seed-adjusted means for both judges (each with its own seed effects), exactly as the overview sets a 12-seed model's tier mean on all 20 seeds."
 },
 "session_agreement": {
  "sessions": 1325,
  "models": 70,
  "excluded_both_at_floor": [
   "claude_fable_5_1::adv_time_pressure_05",
   "claude_opus_5::adv_time_pressure_05",
   "claude_opus_5_5::adv_time_pressure_05"
  ],
  "dimensions": {
   "overall": {
    "n": 1325,
    "pearson": 0.711,
    "spearman": 0.654,
    "pearson_ci95": [
     0.62,
     0.772
    ],
    "spearman_ci95": [
     0.547,
     0.734
    ],
    "mean_diff": 0.939,
    "median_abs_diff": 0.9,
    "within_0_5": 0.236
   },
   "S.5_agency_respect_session": {
    "n": 1325,
    "pearson": 0.473,
    "spearman": 0.376,
    "pearson_ci95": [
     0.385,
     0.544
    ],
    "spearman_ci95": [
     0.269,
     0.472
    ],
    "mean_diff": 1.166,
    "median_abs_diff": 1.0,
    "within_0_5": 0.367
   },
   "S.1_consistency_over_time": {
    "n": 1325,
    "pearson": 0.582,
    "spearman": 0.497,
    "pearson_ci95": [
     0.455,
     0.662
    ],
    "spearman_ci95": [
     0.377,
     0.595
    ],
    "mean_diff": 0.961,
    "median_abs_diff": 1.0,
    "within_0_5": 0.264
   },
   "S.3_narrative_momentum": {
    "n": 1325,
    "pearson": 0.7,
    "spearman": 0.667,
    "pearson_ci95": [
     0.639,
     0.745
    ],
    "spearman_ci95": [
     0.594,
     0.72
    ],
    "mean_diff": 0.88,
    "median_abs_diff": 0.8,
    "within_0_5": 0.346
   }
  }
 },
 "model_agreement": {
  "models": 69,
  "dimensions": {
   "overall": {
    "n": 69,
    "pearson": 0.87,
    "spearman": 0.808,
    "pearson_ci95": [
     0.787,
     0.926
    ],
    "spearman_ci95": [
     0.672,
     0.894
    ],
    "mean_diff": 0.943,
    "median_abs_diff": 0.96,
    "within_0_5": 0.072
   },
   "S.5_agency_respect_session": {
    "n": 69,
    "pearson": 0.596,
    "spearman": 0.44,
    "pearson_ci95": [
     0.417,
     0.718
    ],
    "spearman_ci95": [
     0.191,
     0.651
    ],
    "mean_diff": 1.165,
    "median_abs_diff": 1.23,
    "within_0_5": 0.159
   },
   "S.1_consistency_over_time": {
    "n": 69,
    "pearson": 0.852,
    "spearman": 0.652,
    "pearson_ci95": [
     0.739,
     0.911
    ],
    "spearman_ci95": [
     0.459,
     0.793
    ],
    "mean_diff": 0.962,
    "median_abs_diff": 1.0,
    "within_0_5": 0.058
   },
   "S.3_narrative_momentum": {
    "n": 69,
    "pearson": 0.912,
    "spearman": 0.906,
    "pearson_ci95": [
     0.871,
     0.942
    ],
    "spearman_ci95": [
     0.831,
     0.944
    ],
    "mean_diff": 0.88,
    "median_abs_diff": 0.875,
    "within_0_5": 0.072
   }
  },
  "by_band": {
   "sonnet_A": {
    "n": 37,
    "pearson": 0.083,
    "spearman": 0.109,
    "pearson_ci95": [
     -0.199,
     0.364
    ],
    "spearman_ci95": [
     -0.243,
     0.431
    ],
    "mean_diff": 1.017,
    "median_abs_diff": 1.095,
    "within_0_5": 0.108,
    "label": "Sonnet's A letter (3.8 and above)",
    "sonnet_spread_sd": 0.154,
    "disagreement_rms_after_offset": 0.327,
    "ratio": 2.13
   },
   "below_A": {
    "n": 32,
    "pearson": 0.948,
    "spearman": 0.911,
    "pearson_ci95": [
     0.898,
     0.973
    ],
    "spearman_ci95": [
     0.794,
     0.959
    ],
    "mean_diff": 0.857,
    "median_abs_diff": 0.901,
    "within_0_5": 0.031,
    "label": "below A",
    "sonnet_spread_sd": 0.515,
    "disagreement_rms_after_offset": 0.204,
    "ratio": 0.395
   }
  },
  "by_band_note": "Inside a letter the spread between models is small, so a correlation there is low partly by range restriction. The ratio sets the judges' disagreement (root mean square of the difference after the scale offset) against the spread of Sonnet's means in that band: above 1, the judges disagree more than the models differ (15b's reading)."
 },
 "scale": {
  "offset": {
   "value": 0.943,
   "ci95_model_resampled": [
    0.878,
    1.009
   ],
   "method": "mean over the 69 tiered models of Sonnet's model mean minus ChatGPT's, both on the overview's model + seed fit, each model weighted once (analyze_round4_overview.scale_offset). Adding it to ChatGPT's means gives both judges the same mean across these models, ROUND4_DESIGN 18a's centring.",
   "alternatives": {
    "session_mean_difference": 0.937,
    "median_of_model_differences": 0.96
   }
  },
  "spread": {
   "sonnet_sd_across_models": 0.562,
   "chatgpt_sd_across_models": 0.49,
   "sd_ratio": 0.871,
   "ols_slope_chatgpt_on_sonnet": 0.758,
   "note": "An offset moves every model by the same amount; it does not undo a difference in spread. ChatGPT's model means spread 87% as wide as Sonnet's, so after the offset alone Sonnet's top models sit a little lower under ChatGPT and its bottom models a little higher for that reason alone. The mean-and-sd rescale in `tiers` removes both."
  }
 },
 "models": {
  "aion_3_5": {
   "n_sessions": 20,
   "chatgpt_sessions": 20,
   "n_seeds": 20,
   "basis": "seed_adjusted",
   "group": "other",
   "sonnet": {
    "overall": 4.38,
    "ci95": [
     4.33,
     4.425
    ],
    "interval_reaches_edge": false,
    "tier": "A",
    "S.5_agency_respect_session": 4.84,
    "S.1_consistency_over_time": 4.685,
    "S.3_narrative_momentum": 4.58
   },
   "chatgpt": {
    "overall": 2.905,
    "ci95": [
     2.73,
     3.08
    ],
    "overall_plain": 2.905,
    "tier": "C",
    "overall_after_offset": 3.8479,
    "tier_after_offset": "A",
    "tier_after_rescale": "A",
    "S.5_agency_respect_session": 2.59,
    "S.1_consistency_over_time": 3.49,
    "S.3_narrative_momentum": 3.65
   },
   "difference_after_offset": -0.532,
   "difference_ci95": [
    -0.662,
    -0.403
   ],
   "difference_interval_excludes_zero": true,
   "beyond_band": true,
   "letters_moved": 0,
   "tier_depends_on_judge": false,
   "share_of_seed_draws_letters_differ": 0.226
  },
  "claude_fable_5_1": {
   "n_sessions": 20,
   "chatgpt_sessions": 20,
   "n_seeds": 20,
   "basis": "seed_adjusted",
   "group": "claude",
   "sonnet": {
    "overall": 4.265,
    "ci95": [
     3.875,
     4.505
    ],
    "interval_reaches_edge": false,
    "tier": "A",
    "S.5_agency_respect_session": 4.64,
    "S.1_consistency_over_time": 4.51,
    "S.3_narrative_momentum": 4.295
   },
   "chatgpt": {
    "overall": 3.18,
    "ci95": [
     2.885,
     3.405
    ],
    "overall_plain": 3.18,
    "tier": "C",
    "overall_after_offset": 4.1229,
    "tier_after_offset": "A",
    "tier_after_rescale": "A",
    "S.5_agency_respect_session": 2.875,
    "S.1_consistency_over_time": 3.61,
    "S.3_narrative_momentum": 3.56
   },
   "difference_after_offset": -0.142,
   "difference_ci95": [
    -0.284,
    0.048
   ],
   "difference_interval_excludes_zero": false,
   "beyond_band": false,
   "letters_moved": 0,
   "tier_depends_on_judge": false,
   "share_of_seed_draws_letters_differ": 0.011
  },
  "claude_opus_4_6": {
   "n_sessions": 20,
   "chatgpt_sessions": 20,
   "n_seeds": 20,
   "basis": "seed_adjusted",
   "group": "claude",
   "sonnet": {
    "overall": 4.305,
    "ci95": [
     4.1849,
     4.405
    ],
    "interval_reaches_edge": false,
    "tier": "A",
    "S.5_agency_respect_session": 4.85,
    "S.1_consistency_over_time": 4.49,
    "S.3_narrative_momentum": 4.475
   },
   "chatgpt": {
    "overall": 2.89,
    "ci95": [
     2.66,
     3.105
    ],
    "overall_plain": 2.89,
    "tier": "C",
    "overall_after_offset": 3.8329,
    "tier_after_offset": "A",
    "tier_after_rescale": "A",
    "S.5_agency_respect_session": 2.76,
    "S.1_consistency_over_time": 3.49,
    "S.3_narrative_momentum": 3.475
   },
   "difference_after_offset": -0.472,
   "difference_ci95": [
    -0.675,
    -0.281
   ],
   "difference_interval_excludes_zero": true,
   "beyond_band": true,
   "letters_moved": 0,
   "tier_depends_on_judge": false,
   "share_of_seed_draws_letters_differ": 0.365
  },
  "claude_opus_4_7": {
   "n_sessions": 12,
   "chatgpt_sessions": 12,
   "n_seeds": 12,
   "basis": "seed_adjusted",
   "group": "claude",
   "sonnet": {
    "overall": 4.2938,
    "ci95": [
     4.1953,
     4.3894
    ],
    "interval_reaches_edge": false,
    "tier": "A",
    "S.5_agency_respect_session": 4.9941,
    "S.1_consistency_over_time": 4.4919,
    "S.3_narrative_momentum": 4.3367
   },
   "chatgpt": {
    "overall": 3.0647,
    "ci95": [
     2.7136,
     3.3801
    ],
    "overall_plain": 3.1167,
    "tier": "C",
    "overall_after_offset": 4.0076,
    "tier_after_offset": "A",
    "tier_after_rescale": "A",
    "S.5_agency_respect_session": 2.845,
    "S.1_consistency_over_time": 3.5812,
    "S.3_narrative_momentum": 3.5185
   },
   "difference_after_offset": -0.286,
   "difference_ci95": [
    -0.617,
    0.033
   ],
   "difference_interval_excludes_zero": false,
   "beyond_band": false,
   "letters_moved": 0,
   "tier_depends_on_judge": false,
   "share_of_seed_draws_letters_differ": 0.093
  },
  "claude_opus_4_8": {
   "n_sessions": 20,
   "chatgpt_sessions": 20,
   "n_seeds": 20,
   "basis": "seed_adjusted",
   "group": "claude",
   "sonnet": {
    "overall": 4.265,
    "ci95": [
     4.19,
     4.34
    ],
    "interval_reaches_edge": false,
    "tier": "A",
    "S.5_agency_respect_session": 4.57,
    "S.1_consistency_over_time": 4.58,
    "S.3_narrative_momentum": 4.375
   },
   "chatgpt": {
    "overall": 3.275,
    "ci95": [
     3.11,
     3.435
    ],
    "overall_plain": 3.275,
    "tier": "B",
    "overall_after_offset": 4.2179,
    "tier_after_offset": "A",
    "tier_after_rescale": "A",
    "S.5_agency_respect_session": 2.85,
    "S.1_consistency_over_time": 3.76,
    "S.3_narrative_momentum": 3.625
   },
   "difference_after_offset": -0.047,
   "difference_ci95": [
    -0.18,
    0.083
   ],
   "difference_interval_excludes_zero": false,
   "beyond_band": false,
   "letters_moved": 0,
   "tier_depends_on_judge": false,
   "share_of_seed_draws_letters_differ": 0.0
  },
  "claude_opus_5": {
   "n_sessions": 20,
   "chatgpt_sessions": 20,
   "n_seeds": 20,
   "basis": "seed_adjusted",
   "group": "claude",
   "sonnet": {
    "overall": 4.35,
    "ci95": [
     3.97,
     4.57
    ],
    "interval_reaches_edge": false,
    "tier": "A",
    "S.5_agency_respect_session": 4.55,
    "S.1_consistency_over_time": 4.535,
    "S.3_narrative_momentum": 4.46
   },
   "chatgpt": {
    "overall": 3.14,
    "ci95": [
     2.845,
     3.375
    ],
    "overall_plain": 3.14,
    "tier": "C",
    "overall_after_offset": 4.0829,
    "tier_after_offset": "A",
    "tier_after_rescale": "A",
    "S.5_agency_respect_session": 2.88,
    "S.1_consistency_over_time": 3.575,
    "S.3_narrative_momentum": 3.64
   },
   "difference_after_offset": -0.267,
   "difference_ci95": [
    -0.471,
    -0.027
   ],
   "difference_interval_excludes_zero": true,
   "beyond_band": false,
   "letters_moved": 0,
   "tier_depends_on_judge": false,
   "share_of_seed_draws_letters_differ": 0.013
  },
  "claude_opus_5_5": {
   "n_sessions": 20,
   "chatgpt_sessions": 20,
   "n_seeds": 20,
   "basis": "seed_adjusted",
   "group": "claude",
   "sonnet": {
    "overall": 4.15,
    "ci95": [
     3.785,
     4.365
    ],
    "interval_reaches_edge": true,
    "tier": "A",
    "S.5_agency_respect_session": 4.55,
    "S.1_consistency_over_time": 4.385,
    "S.3_narrative_momentum": 4.185
   },
   "chatgpt": {
    "overall": 3.38,
    "ci95": [
     3.0699,
     3.605
    ],
    "overall_plain": 3.38,
    "tier": "B",
    "overall_after_offset": 4.3229,
    "tier_after_offset": "A",
    "tier_after_rescale": "A",
    "S.5_agency_respect_session": 3.4,
    "S.1_consistency_over_time": 3.825,
    "S.3_narrative_momentum": 3.75
   },
   "difference_after_offset": 0.173,
   "difference_ci95": [
    0.004,
    0.357
   ],
   "difference_interval_excludes_zero": true,
   "beyond_band": false,
   "letters_moved": 0,
   "tier_depends_on_judge": false,
   "share_of_seed_draws_letters_differ": 0.029
  },
  "claude_sonnet_4_5": {
   "n_sessions": 20,
   "chatgpt_sessions": 20,
   "n_seeds": 20,
   "basis": "seed_adjusted",
   "group": "claude",
   "sonnet": {
    "overall": 4.07,
    "ci95": [
     3.995,
     4.145
    ],
    "interval_reaches_edge": false,
    "tier": "A",
    "S.5_agency_respect_session": 4.73,
    "S.1_consistency_over_time": 4.415,
    "S.3_narrative_momentum": 4.205
   },
   "chatgpt": {
    "overall": 2.89,
    "ci95": [
     2.63,
     3.15
    ],
    "overall_plain": 2.89,
    "tier": "C",
    "overall_after_offset": 3.8329,
    "tier_after_offset": "A",
    "tier_after_rescale": "A",
    "S.5_agency_respect_session": 2.96,
    "S.1_consistency_over_time": 3.42,
    "S.3_narrative_momentum": 3.44
   },
   "difference_after_offset": -0.237,
   "difference_ci95": [
    -0.434,
    -0.043
   ],
   "difference_interval_excludes_zero": true,
   "beyond_band": false,
   "letters_moved": 0,
   "tier_depends_on_judge": false,
   "share_of_seed_draws_letters_differ": 0.378
  },
  "claude_sonnet_4_6": {
   "n_sessions": 20,
   "chatgpt_sessions": 20,
   "n_seeds": 20,
   "basis": "seed_adjusted",
   "group": "claude",
   "sonnet": {
    "overall": 4.255,
    "ci95": [
     4.17,
     4.335
    ],
    "interval_reaches_edge": false,
    "tier": "A",
    "S.5_agency_respect_session": 4.8,
    "S.1_consistency_over_time": 4.6,
    "S.3_narrative_momentum": 4.27
   },
   "chatgpt": {
    "overall": 3.07,
    "ci95": [
     2.875,
     3.255
    ],
    "overall_plain": 3.07,
    "tier": "C",
    "overall_after_offset": 4.0129,
    "tier_after_offset": "A",
    "tier_after_rescale": "A",
    "S.5_agency_respect_session": 3.225,
    "S.1_consistency_over_time": 3.465,
    "S.3_narrative_momentum": 3.35
   },
   "difference_after_offset": -0.242,
   "difference_ci95": [
    -0.399,
    -0.085
   ],
   "difference_interval_excludes_zero": true,
   "beyond_band": false,
   "letters_moved": 0,
   "tier_depends_on_judge": false,
   "share_of_seed_draws_letters_differ": 0.006
  },
  "claude_sonnet_5": {
   "n_sessions": 20,
   "chatgpt_sessions": 20,
   "n_seeds": 20,
   "basis": "seed_adjusted",
   "group": "claude",
   "sonnet": {
    "overall": 4.31,
    "ci95": [
     4.1949,
     4.41
    ],
    "interval_reaches_edge": false,
    "tier": "A",
    "S.5_agency_respect_session": 4.77,
    "S.1_consistency_over_time": 4.665,
    "S.3_narrative_momentum": 4.505
   },
   "chatgpt": {
    "overall": 3.165,
    "ci95": [
     2.975,
     3.35
    ],
    "overall_plain": 3.165,
    "tier": "C",
    "overall_after_offset": 4.1079,
    "tier_after_offset": "A",
    "tier_after_rescale": "A",
    "S.5_agency_respect_session": 3.185,
    "S.1_consistency_over_time": 3.57,
    "S.3_narrative_momentum": 3.455
   },
   "difference_after_offset": -0.202,
   "difference_ci95": [
    -0.34,
    -0.059
   ],
   "difference_interval_excludes_zero": true,
   "beyond_band": false,
   "letters_moved": 0,
   "tier_depends_on_judge": false,
   "share_of_seed_draws_letters_differ": 0.0
  },
  "command_a_plus": {
   "n_sessions": 20,
   "chatgpt_sessions": 20,
   "n_seeds": 20,
   "basis": "seed_adjusted",
   "group": "other",
   "sonnet": {
    "overall": 2.29,
    "ci95": [
     2.09,
     2.5
    ],
    "interval_reaches_edge": false,
    "tier": "D",
    "S.5_agency_respect_session": 3.89,
    "S.1_consistency_over_time": 2.76,
    "S.3_narrative_momentum": 2.44
   },
   "chatgpt": {
    "overall": 1.67,
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   "n_seeds": 20,
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     2.775
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     2.96
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   "tier_depends_on_judge": false,
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   "difference_interval_excludes_zero": true,
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   "letters_moved": 0,
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  },
  "tencent_hy4": {
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   "n_seeds": 20,
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   "difference_interval_excludes_zero": false,
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   "letters_moved": 0,
   "tier_depends_on_judge": false,
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  },
  "unslopnemo_12b": {
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   "n_seeds": 20,
   "basis": "seed_adjusted",
   "group": "other",
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     2.73
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    "interval_reaches_edge": true,
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   ],
   "difference_interval_excludes_zero": true,
   "beyond_band": false,
   "letters_moved": 1,
   "tier_depends_on_judge": true,
   "share_of_seed_draws_letters_differ": 0.726
  },
  "venice_dolphin_24b": {
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   "basis": "seed_adjusted",
   "group": "other",
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   },
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    "tier": "E",
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   },
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   "difference_ci95": [
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   ],
   "difference_interval_excludes_zero": true,
   "beyond_band": false,
   "letters_moved": 1,
   "tier_depends_on_judge": true,
   "share_of_seed_draws_letters_differ": 0.702
  }
 },
 "tiers": {
  "letters": {
   "A": "3.8 and above",
   "B": "3.2-3.8",
   "C": "2.6-3.2",
   "D": "2.0-2.6",
   "E": "below 2.0"
  },
  "sonnet_sizes": {
   "A": 37,
   "B": 22,
   "C": 3,
   "D": 7
  },
  "models": 69,
  "raw": {
   "same_letter": 1,
   "sizes": {
    "A": 1,
    "B": 8,
    "C": 41,
    "D": 11,
    "E": 8
   },
   "confusion": {
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     "A": 1,
     "B": 8,
     "C": 28
    },
    "B": {
     "C": 13,
     "D": 9
    },
    "C": {
     "D": 2,
     "E": 1
    },
    "D": {
     "E": 7
    }
   },
   "note": "ChatGPT's own letters on the same fixed ranges, raw: they sit lower because ChatGPT uses the scale lower"
  },
  "after_offset": {
   "same_letter": 50,
   "sizes": {
    "A": 33,
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   },
   "confusion": {
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    },
    "B": {
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     "B": 17,
     "C": 2
    },
    "C": {
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     "C": 1
    },
    "D": {
     "C": 5,
     "D": 2
    }
   },
   "tier_depends_on_judge": [
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    "deepseek_r1_0528",
    "gemini_3_1_pro",
    "glm_5_3_prime",
    "gpt_4_1",
    "grok_4_3",
    "grok_4_7",
    "hemmingway_1",
    "llama_4_maverick",
    "lunaris_8b",
    "magnum_v4_72b",
    "mimo_2_5_pro",
    "mimo_2_6_flash",
    "minimax_m2_7",
    "minimax_m3",
    "mistral_small_creative",
    "qwen3_6_35b_a3b",
    "unslopnemo_12b",
    "venice_dolphin_24b"
   ],
   "moves": [
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     "model": "hemmingway_1",
     "sonnet_tier": "A",
     "chatgpt_tier_after_offset": "B",
     "letters_moved": -1,
     "direction": "lower under ChatGPT",
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     "beyond_band": true,
     "difference_interval_excludes_zero": true,
     "sonnet_interval_reaches_edge": false,
     "share_of_seed_draws_letters_differ": 0.991,
     "group": "other"
    },
    {
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     "share_of_seed_draws_letters_differ": 0.991,
     "group": "other"
    },
    {
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     "share_of_seed_draws_letters_differ": 0.952,
     "group": "other"
    },
    {
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     "share_of_seed_draws_letters_differ": 0.863,
     "group": "other"
    },
    {
     "model": "llama_4_maverick",
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     "group": "other"
    },
    {
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     "group": "other"
    },
    {
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     "group": "other"
    },
    {
     "model": "lunaris_8b",
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     "group": "other"
    },
    {
     "model": "unslopnemo_12b",
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     "group": "other"
    },
    {
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     "group": "other"
    },
    {
     "model": "venice_dolphin_24b",
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     "group": "other"
    },
    {
     "model": "mimo_2_5_pro",
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     "group": "other"
    },
    {
     "model": "minimax_m2_7",
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     "group": "other"
    },
    {
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     "share_of_seed_draws_letters_differ": 0.509,
     "group": "other"
    },
    {
     "model": "mistral_small_creative",
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     "group": "other"
    },
    {
     "model": "gpt_4_1",
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     "direction": "higher under ChatGPT",
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     "share_of_seed_draws_letters_differ": 0.612,
     "group": "openai"
    },
    {
     "model": "qwen3_6_35b_a3b",
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     "chatgpt_tier_after_offset": "B",
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     "direction": "higher under ChatGPT",
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     "share_of_seed_draws_letters_differ": 0.336,
     "group": "other"
    },
    {
     "model": "grok_4_3",
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     "direction": "lower under ChatGPT",
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     "beyond_band": false,
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     "share_of_seed_draws_letters_differ": 0.322,
     "group": "other"
    },
    {
     "model": "grok_4_7",
     "sonnet_tier": "B",
     "chatgpt_tier_after_offset": "A",
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     "direction": "higher under ChatGPT",
     "difference_after_offset": 0.033,
     "difference_ci95": [
      -0.156,
      0.228
     ],
     "beyond_band": false,
     "difference_interval_excludes_zero": false,
     "sonnet_interval_reaches_edge": true,
     "share_of_seed_draws_letters_differ": 0.236,
     "group": "other"
    }
   ],
   "counts": {
    "moved": 19,
    "higher_under_chatgpt": 10,
    "lower_under_chatgpt": 9,
    "beyond_band": 7,
    "difference_interval_excludes_zero": 14,
    "sonnet_interval_reaches_edge": 12,
    "letters_differ_in_90pct_of_seed_draws": 4,
    "letters_differ_in_under_half_of_seed_draws": 3,
    "by_group": {
     "openai": 1,
     "other": 18
    }
   },
   "rule": "ChatGPT's mean plus the scale offset, on the same fixed letters; a model whose letter differs from Sonnet's is `tier_depends_on_judge` (the overview's flag). `share_of_seed_draws_letters_differ` is how often the two letters differ across the seed bootstrap (offset re-estimated in each draw)."
  },
  "after_rescale": {
   "same_letter": 53,
   "moved": [
    "deepseek_r1_0528",
    "gemini_3_1_pro",
    "glm_5_3_prime",
    "gpt_4_1",
    "grok_4_3",
    "grok_4_7",
    "hemmingway_1",
    "llama_4_maverick",
    "lunaris_8b",
    "magnum_v4_72b",
    "mimo_2_5_pro",
    "mimo_2_6_flash",
    "minimax_m2_7",
    "minimax_m3",
    "mistral_small_creative",
    "unslopnemo_12b"
   ],
   "note": "Sensitivity: ChatGPT's model means rescaled to Sonnet's mean and sd across models, which also undoes the difference in spread"
  }
 },
 "vendor_premiums": {
  "claude_sonnet_over_chatgpt": {
   "group": "Claude models (claude_*)",
   "sessions": 1325,
   "group_sessions": 169,
   "group_models": 9,
   "models": 70,
   "regression": {
    "what": "Sonnet score on [1, ChatGPT score, its square, group]: how much higher Sonnet scores the group's sessions than sessions ChatGPT scored the same",
    "coefficient": 0.379,
    "se": 0.036,
    "t": 10.5,
    "ci95_model_resampled": [
     0.296,
     0.47
    ]
   },
   "reverse_regression": {
    "what": "ChatGPT score on [1, Sonnet score, its square, group]: a premium that is Sonnet's alone shows here as a negative coefficient; a positive one means the forward regression carries a regression-to-the-mean share (the group is also better by ChatGPT)",
    "coefficient": -0.006,
    "se": 0.042,
    "t": -0.1,
    "ci95_model_resampled": [
     -0.177,
     0.156
    ]
   },
   "rescaled_difference": {
    "what": "Sonnet minus ChatGPT rescaled to Sonnet's mean and sd, group minus the rest: direction-free (the overview's tilt)",
    "vs_rest": 0.209,
    "vs_all_sessions": 0.183,
    "ci95_model_resampled": [
     0.056,
     0.355
    ]
   },
   "note": null
  },
  "openai_chatgpt_over_sonnet": {
   "group": "OpenAI models (gpt_*)",
   "sessions": 1325,
   "group_sessions": 140,
   "group_models": 7,
   "models": 70,
   "regression": {
    "what": "ChatGPT score on [1, Sonnet score, its square, group]: how much higher ChatGPT scores the group's sessions than sessions Sonnet scored the same",
    "coefficient": 0.616,
    "se": 0.038,
    "t": 16.3,
    "ci95_model_resampled": [
     0.408,
     0.808
    ]
   },
   "reverse_regression": {
    "what": "Sonnet score on [1, ChatGPT score, its square, group]: a premium that is ChatGPT's alone shows here as a negative coefficient; a positive one means the forward regression carries a regression-to-the-mean share (the group is also better by Sonnet)",
    "coefficient": -0.15,
    "se": 0.045,
    "t": -3.3,
    "ci95_model_resampled": [
     -0.243,
     -0.053
    ]
   },
   "rescaled_difference": {
    "what": "ChatGPT minus Sonnet rescaled to ChatGPT's mean and sd, group minus the rest: direction-free (the overview's tilt)",
    "vs_rest": 0.52,
    "vs_all_sessions": 0.465,
    "ci95_model_resampled": [
     0.345,
     0.694
    ]
   },
   "note": null
  },
  "gpt_6_chatgpt_over_sonnet": {
   "group": "the GPT-6 family (gpt_6_*)",
   "sessions": 1325,
   "group_sessions": 100,
   "group_models": 5,
   "models": 70,
   "regression": {
    "what": "ChatGPT score on [1, Sonnet score, its square, group]: how much higher ChatGPT scores the group's sessions than sessions Sonnet scored the same",
    "coefficient": 0.742,
    "se": 0.044,
    "t": 17.0,
    "ci95_model_resampled": [
     0.602,
     0.867
    ]
   },
   "reverse_regression": {
    "what": "Sonnet score on [1, ChatGPT score, its square, group]: a premium that is ChatGPT's alone shows here as a negative coefficient; a positive one means the forward regression carries a regression-to-the-mean share (the group is also better by Sonnet)",
    "coefficient": -0.161,
    "se": 0.054,
    "t": -3.0,
    "ci95_model_resampled": [
     -0.261,
     -0.033
    ]
   },
   "rescaled_difference": {
    "what": "ChatGPT minus Sonnet rescaled to ChatGPT's mean and sd, group minus the rest: direction-free (the overview's tilt)",
    "vs_rest": 0.635,
    "vs_all_sessions": 0.587,
    "ci95_model_resampled": [
     0.517,
     0.757
    ]
   },
   "note": null
  },
  "gpt_6_astra_chatgpt_over_sonnet": {
   "group": "gpt_6_astra alone",
   "sessions": 1325,
   "group_sessions": 20,
   "group_models": 1,
   "models": 70,
   "regression": {
    "what": "ChatGPT score on [1, Sonnet score, its square, group]: how much higher ChatGPT scores the group's sessions than sessions Sonnet scored the same",
    "coefficient": 0.831,
    "se": 0.101,
    "t": 8.2,
    "ci95_model_resampled": null
   },
   "reverse_regression": {
    "what": "Sonnet score on [1, ChatGPT score, its square, group]: a premium that is ChatGPT's alone shows here as a negative coefficient; a positive one means the forward regression carries a regression-to-the-mean share (the group is also better by Sonnet)",
    "coefficient": -0.112,
    "se": 0.105,
    "t": -1.1,
    "ci95_model_resampled": null
   },
   "rescaled_difference": {
    "what": "ChatGPT minus Sonnet rescaled to ChatGPT's mean and sd, group minus the rest: direction-free (the overview's tilt)",
    "vs_rest": 0.734,
    "vs_all_sessions": 0.723,
    "ci95_model_resampled": null
   },
   "note": "one model: no model-resampled interval; the session SE treats its 20 sessions as independent"
  },
  "claude_letter_check": {
   "regression": {
    "shift": -0.379,
    "claude_models": 9,
    "claude_models_changing_letter": 2,
    "changes": [
     {
      "model": "claude_opus_5_5",
      "from_tier": "A",
      "to_tier": "B",
      "mean_after": 3.771
     },
     {
      "model": "claude_sonnet_4_5",
      "from_tier": "A",
      "to_tier": "B",
      "mean_after": 3.691
     }
    ]
   },
   "regression_interval_upper": {
    "shift": -0.47,
    "claude_models": 9,
    "claude_models_changing_letter": 5,
    "changes": [
     {
      "model": "claude_fable_5_1",
      "from_tier": "A",
      "to_tier": "B",
      "mean_after": 3.795
     },
     {
      "model": "claude_opus_4_8",
      "from_tier": "A",
      "to_tier": "B",
      "mean_after": 3.795
     },
     {
      "model": "claude_opus_5_5",
      "from_tier": "A",
      "to_tier": "B",
      "mean_after": 3.68
     },
     {
      "model": "claude_sonnet_4_5",
      "from_tier": "A",
      "to_tier": "B",
      "mean_after": 3.6
     },
     {
      "model": "claude_sonnet_4_6",
      "from_tier": "A",
      "to_tier": "B",
      "mean_after": 3.785
     }
    ]
   },
   "rescaled_difference": {
    "shift": -0.209,
    "claude_models": 9,
    "claude_models_changing_letter": 0,
    "changes": []
   },
   "rescaled_difference_interval_upper": {
    "shift": -0.355,
    "claude_models": 9,
    "claude_models_changing_letter": 2,
    "changes": [
     {
      "model": "claude_opus_5_5",
      "from_tier": "A",
      "to_tier": "B",
      "mean_after": 3.795
     },
     {
      "model": "claude_sonnet_4_5",
      "from_tier": "A",
      "to_tier": "B",
      "mean_after": 3.715
     }
    ]
   }
  },
  "openai_letter_check": {
   "shift": -0.616,
   "openai_models": 7,
   "tier_depends_before": [
    "gpt_4_1"
   ],
   "tier_depends_after": [
    "gpt_5_5",
    "gpt_6_luna"
   ],
   "differences_after": {
    "gpt_4_1": -0.421,
    "gpt_5_5": -0.376,
    "gpt_6_astra": 0.154,
    "gpt_6_luna": -0.161,
    "gpt_6_luna_pro": 0.009,
    "gpt_6_sol": -0.021,
    "gpt_6_sol_pro": 0.114
   }
  }
 },
 "bridge": {
  "n": 24,
  "sessions": [
   "claude_fable_5_1::adv_pov_tense_action_14",
   "claude_fable_5_1::adv_sysprompt_speech_pattern_15",
   "claude_sonnet_4_5::adv_sysprompt_speech_pattern_15",
   "deepseek_v4_1_flash::adv_bigcard_rules_overload_20",
   "deepseek_v4_flash::adv_agency_romance_11",
   "gemini_3_1_flash_lite::adv_pov_multi_npc_13",
   "gemini_3_7_flash::adv_bigcard_buried_details_18",
   "glm_4_7::adv_sysprompt_forbidden_topic_17",
   "glm_5_3_flashx::adv_bigcard_buried_details_18",
   "gpt_6_astra::adv_bigcard_relationship_web_19",
   "gpt_6_sol::adv_agency_romance_11",
   "gpt_6_sol_pro::adv_pov_second_person_12",
   "hemmingway_1::adv_bigcard_buried_details_18",
   "magnum_v4_72b::adv_pov_second_person_12",
   "mimo_2_6_flash::adv_passive_user_03",
   "minimax_m3::adv_subtle_ooc_06",
   "qwen3_5_flash::adv_passive_user_03",
   "qwen3_6_27b::adv_sysprompt_style_restriction_16",
   "qwen3_6_35b_a3b::adv_subtle_ooc_06",
   "qwen3_7_max::adv_contradictory_lore_02",
   "qwen3_8_max_prime::adv_agency_emotional_climax_09",
   "tencent_hy4::adv_bigcard_relationship_web_19",
   "unslopnemo_12b::adv_character_break_bait_07",
   "venice_dolphin_24b::adv_agency_combat_10"
  ],
  "app_vs_agent": {
   "pearson": 0.89,
   "mean_diff_app_minus_agent": -0.083,
   "median_abs_diff": 0.2,
   "within_0_5": 0.958
  },
  "sonnet_vs_app": {
   "pearson": 0.673,
   "mean_diff": 0.825
  },
  "sonnet_vs_agent": {
   "pearson": 0.694,
   "mean_diff": 0.742
  },
  "references": {
   "chatgpt_same_harness": {
    "r": 0.935,
    "median_abs_diff": 0.15,
    "source": "ROUND4_DESIGN 17c: the two earlier ChatGPT passes (labels visible, then blind), 120 sessions"
   },
   "gemini_harness_shift": {
    "mean_diff": -0.39,
    "r": 0.958,
    "source": "ROUND4_DESIGN 18c: Gemini chat client vs API, same sessions"
   }
  },
  "reading": "Two ChatGPT runs on the same text: the Codex pass (`app` in the key names) and the earlier blind passes (`agent`; judge_round2_chatgpt, judge_inc1_chatgpt). Each run was a coordinator handing its work to clean-context raters, so this compares two runs with different rater sets; where the earlier passes ran is not recorded. The level barely moves (mean difference -0.08, Codex minus earlier) and the two runs agree at r +0.89, a little below the +0.935 of the two earlier passes on the 120-session sample (17c); Gemini moved -0.39 between its chat-client and API passes (18c). Mixing the 179 reused rows into the corpus is therefore a small effect, and `sensitivity` shows the figures without them. n=24 is small."
 },
 "sensitivity": {
  "all_rows": {
   "sessions": 1328,
   "session_pearson_overall": 0.711,
   "session_pearson_overall_ci95": [
    0.62,
    0.772
   ],
   "model_pearson_overall": 0.87,
   "model_pearson_overall_ci95": [
    0.787,
    0.926
   ],
   "scale_offset": 0.943,
   "raw_same_letter": 1,
   "same_letter_after_offset": 50,
   "tier_depends_on_judge": [
    "command_a_plus",
    "deepseek_r1_0528",
    "gemini_3_1_pro",
    "glm_5_3_prime",
    "gpt_4_1",
    "grok_4_3",
    "grok_4_7",
    "hemmingway_1",
    "llama_4_maverick",
    "lunaris_8b",
    "magnum_v4_72b",
    "mimo_2_5_pro",
    "mimo_2_6_flash",
    "minimax_m2_7",
    "minimax_m3",
    "mistral_small_creative",
    "qwen3_6_35b_a3b",
    "unslopnemo_12b",
    "venice_dolphin_24b"
   ],
   "claude_premium_regression": 0.379,
   "claude_premium_regression_ci95": [
    0.296,
    0.47
   ],
   "claude_premium_rescaled": 0.209,
   "openai_premium_regression": 0.616,
   "openai_premium_regression_ci95": [
    0.408,
    0.808
   ],
   "openai_premium_rescaled": 0.52,
   "what": "every session: 1149 Codex rows and 179 rows reused from the earlier blind passes; bridge sessions carry the Codex row",
   "tier_depends_changes_vs_all_rows": {
    "added": [],
    "removed": []
   }
  },
  "without_reused_rows": {
   "sessions": 1149,
   "session_pearson_overall": 0.714,
   "session_pearson_overall_ci95": [
    0.623,
    0.774
   ],
   "model_pearson_overall": 0.866,
   "model_pearson_overall_ci95": [
    0.78,
    0.923
   ],
   "scale_offset": 0.954,
   "raw_same_letter": 1,
   "same_letter_after_offset": 49,
   "tier_depends_on_judge": [
    "command_a_plus",
    "deepseek_r1_0528",
    "deepseek_v3_0324",
    "glm_4_7",
    "glm_5_3_prime",
    "gpt_4_1",
    "grok_4_7",
    "hemmingway_1",
    "llama_4_maverick",
    "lunaris_8b",
    "magnum_v4_72b",
    "mimo_2_5_pro",
    "mimo_2_6_flash",
    "minimax_m2_7",
    "minimax_m3",
    "mistral_small_creative",
    "qwen3_6_35b_a3b",
    "qwen3_8_max_prime",
    "unslopnemo_12b",
    "venice_dolphin_24b"
   ],
   "claude_premium_regression": 0.378,
   "claude_premium_regression_ci95": [
    0.29,
    0.469
   ],
   "claude_premium_rescaled": 0.209,
   "openai_premium_regression": 0.615,
   "openai_premium_regression_ci95": [
    0.382,
    0.836
   ],
   "openai_premium_rescaled": 0.512,
   "what": "Codex rows only: the 179 reused rows from the earlier passes dropped",
   "tier_depends_changes_vs_all_rows": {
    "added": [
     "deepseek_v3_0324",
     "glm_4_7",
     "qwen3_8_max_prime"
    ],
    "removed": [
     "gemini_3_1_pro",
     "grok_4_3"
    ]
   }
  },
  "without_bridge_sessions": {
   "sessions": 1304,
   "session_pearson_overall": 0.712,
   "session_pearson_overall_ci95": [
    0.621,
    0.773
   ],
   "model_pearson_overall": 0.871,
   "model_pearson_overall_ci95": [
    0.787,
    0.926
   ],
   "scale_offset": 0.943,
   "raw_same_letter": 0,
   "same_letter_after_offset": 50,
   "tier_depends_on_judge": [
    "command_a_plus",
    "deepseek_r1_0528",
    "gemini_3_1_pro",
    "glm_5_3_prime",
    "gpt_4_1",
    "grok_4_3",
    "grok_4_7",
    "hemmingway_1",
    "llama_4_maverick",
    "lunaris_8b",
    "magnum_v4_72b",
    "mimo_2_5_pro",
    "mimo_2_6_flash",
    "minimax_m2_7",
    "minimax_m3",
    "mistral_small_creative",
    "qwen3_6_35b_a3b",
    "unslopnemo_12b",
    "venice_dolphin_24b"
   ],
   "claude_premium_regression": 0.38,
   "claude_premium_regression_ci95": [
    0.297,
    0.47
   ],
   "claude_premium_rescaled": 0.204,
   "openai_premium_regression": 0.608,
   "openai_premium_regression_ci95": [
    0.404,
    0.801
   ],
   "openai_premium_rescaled": 0.515,
   "what": "the 24 bridge sessions dropped",
   "tier_depends_changes_vs_all_rows": {
    "added": [],
    "removed": []
   }
  },
  "app_rows_without_bridge": {
   "sessions": 1125,
   "session_pearson_overall": 0.715,
   "session_pearson_overall_ci95": [
    0.624,
    0.775
   ],
   "model_pearson_overall": 0.866,
   "model_pearson_overall_ci95": [
    0.78,
    0.923
   ],
   "scale_offset": 0.954,
   "raw_same_letter": 1,
   "same_letter_after_offset": 50,
   "tier_depends_on_judge": [
    "command_a_plus",
    "deepseek_r1_0528",
    "deepseek_v3_0324",
    "glm_4_7",
    "glm_5_3_prime",
    "gpt_4_1",
    "grok_4_7",
    "hemmingway_1",
    "llama_4_maverick",
    "lunaris_8b",
    "magnum_v4_72b",
    "mimo_2_5_pro",
    "mimo_2_6_flash",
    "minimax_m2_7",
    "minimax_m3",
    "mistral_small_creative",
    "qwen3_6_35b_a3b",
    "unslopnemo_12b",
    "venice_dolphin_24b"
   ],
   "claude_premium_regression": 0.378,
   "claude_premium_regression_ci95": [
    0.287,
    0.469
   ],
   "claude_premium_rescaled": 0.203,
   "openai_premium_regression": 0.606,
   "openai_premium_regression_ci95": [
    0.38,
    0.827
   ],
   "openai_premium_rescaled": 0.505,
   "what": "Codex rows only, bridge sessions dropped",
   "tier_depends_changes_vs_all_rows": {
    "added": [
     "deepseek_v3_0324",
     "glm_4_7"
    ],
    "removed": [
     "gemini_3_1_pro",
     "grok_4_3"
    ]
   }
  },
  "bridge_on_agent_rows": {
   "sessions": 1328,
   "session_pearson_overall": 0.711,
   "session_pearson_overall_ci95": [
    0.62,
    0.772
   ],
   "model_pearson_overall": 0.87,
   "model_pearson_overall_ci95": [
    0.786,
    0.925
   ],
   "scale_offset": 0.941,
   "raw_same_letter": 0,
   "same_letter_after_offset": 50,
   "tier_depends_on_judge": [
    "command_a_plus",
    "deepseek_r1_0528",
    "gemini_3_1_pro",
    "glm_5_3_prime",
    "gpt_4_1",
    "grok_4_3",
    "grok_4_7",
    "hemmingway_1",
    "llama_4_maverick",
    "lunaris_8b",
    "magnum_v4_72b",
    "mimo_2_5_pro",
    "mimo_2_6_flash",
    "minimax_m2_7",
    "minimax_m3",
    "mistral_small_creative",
    "qwen3_6_35b_a3b",
    "unslopnemo_12b",
    "venice_dolphin_24b"
   ],
   "claude_premium_regression": 0.377,
   "claude_premium_regression_ci95": [
    0.294,
    0.467
   ],
   "claude_premium_rescaled": 0.203,
   "openai_premium_regression": 0.611,
   "openai_premium_regression_ci95": [
    0.405,
    0.803
   ],
   "openai_premium_rescaled": 0.516,
   "what": "every session, the bridge sessions on their row from the earlier passes",
   "tier_depends_changes_vs_all_rows": {
    "added": [],
    "removed": []
   }
  }
 },
 "earlier": {
  "session_r_overall": {
   "value": 0.716,
   "n": 117,
   "source": "ROUND4_DESIGN 17a: the blind ChatGPT pass on the 120-session sample"
  },
  "model_r_overall": {
   "value": 0.797,
   "n": null,
   "source": "ROUND4_DESIGN 18: sonnet vs chatgpt per model on that sample"
  },
  "mean_gap": {
   "value": 0.77,
   "source": "ROUND4_DESIGN 17a/18: Sonnet minus ChatGPT, blind pass, 120-session sample"
  },
  "claude_tilt": {
   "value": 0.2,
   "ci95": [
    -0.013,
    0.406
   ],
   "n": 203,
   "source": "round4_overview.json checks.self_preference: Sonnet over ChatGPT, Claude minus non-Claude, rescaled"
  },
  "claude_premium_change": {
   "value": 0.304,
   "ci95": [
    0.138,
    0.466
   ],
   "n": 110,
   "source": "round4_continuity.json (before this file): new judge minus old judge, Claude coefficient vs ChatGPT, stored old scores"
  },
  "openai_gap": {
   "value": 0.57,
   "n": 7,
   "source": "ROUND4_DESIGN 17b: OpenAI against the rest, blind pass, 7 OpenAI sessions"
  }
 },
 "method": {
  "session_set": "sessions both judges scored on the current text (hash-checked); for agreement, sessions both judges put at the 1.0 floor are left out (no model text to judge, compare_external_judge.py's rule); for the vendor terms, blank scenes are left out (the continuity check's rule)",
  "model_means": "the overview's model + seed fit over the tiered pool, each judge with its own seed effects (analyze_round4_overview.seed_adjusted_means); untiered models get plain means",
  "spearman": "average ranks for ties",
  "model_resampling": "4000 draws, numpy default_rng(20260928): models drawn with replacement, every session of a drawn model comes along; the same draws for every figure computed on one session set",
  "seed_bootstrap": "10000 draws replaying the overview's own (numpy default_rng(20260926)), both judges on each draw; the offset is re-estimated in each draw",
  "groups": {
   "claude": "Claude models (claude_*)",
   "openai": "OpenAI models (gpt_*)",
   "gpt_6": "the GPT-6 family (gpt_6_*)",
   "gpt_6_astra": "gpt_6_astra alone"
  }
 },
 "inputs": {
  "craft_baseline_20260921_125936.json": "04da84eed4affc53",
  "craft_baseline_20260921_174824.json": "3f4c94d84b2f05ef",
  "craft_baseline_20260924_122936.json": "09c7fd3c6e91f8bc",
  "craft_baseline_20260924_123104.json": "4de926c1ec681d8a",
  "craft_baseline_20260924_143626.json": "0fe0e4b77888365f",
  "craft_baseline_20260924_224934.json": "5cdc00596feb3133",
  "craft_baseline_20260924_231143.json": "5d810de4576db4e0",
  "craft_baseline_20260926_050941.json": "85ca536deeab078a",
  "judge_full_chatgpt/_manifest.json": "9e805f6094f8642b",
  "judge_full_chatgpt/merged/_manifest.json": "2b7fe262127d13ea",
  "judge_full_chatgpt/merged/external_part_app.json": "e0b5e432f47214a6",
  "judge_full_chatgpt/merged/external_part_reused_inc1_chatgpt.json": "a3643f112bf7a753",
  "judge_full_chatgpt/merged/external_part_reused_round2_chatgpt.json": "6ff475f055c27932",
  "judge_inc1_chatgpt/external_blind_pass/external_part01.json": "af1edad01901ea0c",
  "judge_inc1_chatgpt/external_blind_pass/external_part02.json": "a746a61ec6a280f9",
  "judge_inc1_chatgpt/external_blind_pass/external_part03.json": "c12127bf8fb8d335",
  "judge_inc1_chatgpt/external_blind_pass/external_part06.json": "fc69eefee92451b1",
  "judge_inc1_chatgpt/external_blind_pass/external_part08.json": "92959917548d1653",
  "judge_inc1_chatgpt/external_blind_pass/external_part10.json": "1fe36f96a8848025",
  "judge_round2_chatgpt/external_blind_pass/external_part02.json": "1f1a6324f80ad734",
  "judge_round2_chatgpt/external_blind_pass/external_part04.json": "573913d382bfb9c7",
  "judge_round2_chatgpt/external_blind_pass/external_part05.json": "1a4aabf027b84a09",
  "judge_round2_chatgpt/external_blind_pass/external_part06.json": "bc57aaed45529f0f",
  "judge_round2_chatgpt/external_blind_pass/external_part07.json": "8911712cd77edcd5",
  "judge_round2_chatgpt/external_blind_pass/external_part08.json": "42bc053fdd182921",
  "judge_round2_chatgpt/external_blind_pass/external_part11.json": "4d4dd954a25126a3",
  "judge_round2_chatgpt/external_blind_pass/external_part12.json": "ddea6ae9126f7d3d",
  "multiturn_merged_all_v2.json": "8f0b319b2ffe6a4d",
  "session_judge_v2.jsonl": "af47ffaf6ad2478a"
 },
 "reading": {
  "can_establish": [
   "Both families order the models alike at the broad scale: per model Pearson +0.87 [0.79, 0.93] and Spearman +0.81 [0.67, 0.89] over 69 models; per session Pearson +0.71 [0.62, 0.77] over 1,325 sessions, where Sonnet against itself gave +0.908 (ROUND4_DESIGN 17c).",
   "ChatGPT uses the scale 0.94 [0.88, 1.01] lower than Sonnet (one offset for every model), and its model means spread 87% as wide. Its raw letters therefore sit lower: on the same fixed ranges, raw, 1 of 69 models get Sonnet's letter.",
   "After that offset 50 of 69 models keep their letter and 19 change (10 higher under ChatGPT, 9 lower). 7 of the 19 differ from Sonnet by more than the card's 0.3 band, 14 have a seed-bootstrap interval of the difference that excludes zero, and 12 already have a Sonnet interval that reaches a letter edge on its own. Across the seed bootstrap the two letters differ in at least 90% of draws for 4 of them and in under half for 3, so the list's edge cases are not firm. Rescaling for spread as well leaves 53 with the same letter.",
   "Inside Sonnet's A letter the two judges agree less (Pearson +0.08 [-0.20, 0.36], n=37; below A +0.95 [0.90, 0.97], n=32). Inside A their disagreement is 2.13 times the spread between the models (below A 0.40): the order inside A depends on the judge, as 15b found on the sample.",
   "ChatGPT scores OpenAI models' sessions +0.62 [0.41, 0.81] above sessions Sonnet scored the same (140 of 1,325 sessions, 7 models); +0.52 [0.34, 0.69] on the direction-free rescaled difference. The reverse regression points the same way (-0.15 [-0.24, -0.05]: Sonnet scores those sessions lower than ChatGPT at the same score predicts), so the difference survives both directions.",
   "Sonnet scores Claude models' sessions +0.38 [0.30, 0.47] above sessions ChatGPT scored the same (169 of 1,325 sessions, 9 models); +0.21 [0.06, 0.35] on the direction-free rescaled difference. The reverse regression gives -0.01 [-0.18, 0.16], not the negative figure a difference that is Sonnet's alone would give, so part of the forward figure is the regression's own artifact (the group scores above the rest under ChatGPT as well); the direction-free rescaled difference is the better guide to its size. Subtracting the forward figure from every Claude session moves 2 of 9 Claude models to another letter; subtracting the rescaled one moves 0."
  ],
  "cannot_establish": [
   "Which judge is right. Neither is a ground truth, the rubric's calibration sentence fits both readings (15a, 18), and the human arena covers 19 models on 12 seeds. A vendor term measured between two judges is relative: it cannot say whether one judge is generous to its own family or the other harsh to it.",
   "Whether a vendor-linked difference is favouritism or a style preference the other judge does not share. Both judges were blind to model names, so it is not the label; each could still recognise a style. Taking ChatGPT's measured OpenAI term off the OpenAI sessions changes which OpenAI models' letters depend on the judge from gpt_4_1 to gpt_5_5, gpt_6_luna.",
   "ChatGPT's self-consistency on the full corpus. Each session was scored once; the 24 bridge sessions (two runs) and 17c's 120 are the only repeats.",
   "Which ChatGPT model served the Codex pass. Codex did not record it. The first ChatGPT pass was recorded as ChatGPT (Astra) (sec 15), so `gpt_6_astra` may be the judge's own model."
  ],
  "round4_tiers": [
   "The published letter stays Sonnet's, on its fixed ranges; nothing is adjusted by this file. `tier_depends_on_judge` marks the 19 models whose letter the other family would not give once its scale offset is removed: for them the letter says as much about the judge as about the model.",
   "Claude models among them: none. OpenAI models among them: gpt_4_1."
  ]
 }
}