add score-chart success-bonus selector diagnostic

runs/ctt_base_context_obs_learned_dominance_score_chartcompat_successbonus2_task_envclip_k16_train_to_test/command.txt

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+python scripts/eval_learned_dominance_selector.py --calibration-input runs/ctt_base_context_obs_train_cal_envclip_k16_rollout_comparison/combined_measured_candidates.json --calibration-target-index data/cil_charts_rgb_refs/train/index.json --eval-input runs/ctt_base_context_obs_test_envclip_k16_rollout_comparison/combined_measured_candidates.json --eval-target-index data/cil_charts_rgb_refs/test/index.json --source-index data/cil_charts_rgb_refs/train/index.json --checkpoint-template runs/ctt_residual_base_context_obs_seed{seed}/model.pt --out-dir runs/ctt_base_context_obs_learned_dominance_score_chartcompat_successbonus2_task_envclip_k16_train_to_test --feature-set score_chart_compat --selector-chart-feature-mode base_context_obs --target success_weighted_margin --success-bonus 2.0 --threshold-scope task --k 16 --bootstrap-samples 300 --no-markdown-report

runs/ctt_base_context_obs_learned_dominance_score_chartcompat_successbonus2_task_envclip_k16_train_to_test/config.yaml

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+bootstrap_samples: 300
+calibration_input: runs/ctt_base_context_obs_train_cal_envclip_k16_rollout_comparison/combined_measured_candidates.json
+calibration_target_index: data/cil_charts_rgb_refs/train/index.json
+checkpoint_template: runs/ctt_residual_base_context_obs_seed{seed}/model.pt
+eval_input: runs/ctt_base_context_obs_test_envclip_k16_rollout_comparison/combined_measured_candidates.json
+eval_target_index: data/cil_charts_rgb_refs/test/index.json
+feature_set: score_chart_compat
+fit_objective: pointwise
+k: 16
+no_markdown_report: True
+out_dir: runs/ctt_base_context_obs_learned_dominance_score_chartcompat_successbonus2_task_envclip_k16_train_to_test
+pairwise_weight: 1.0
+ridge_lambdas: 0,0.01,0.1,1,10,100
+selector_chart_feature_mode: base_context_obs
+source_index: data/cil_charts_rgb_refs/train/index.json
+success_bonus: 2.0
+target: success_weighted_margin
+threshold_scope: task

runs/ctt_base_context_obs_learned_dominance_score_chartcompat_successbonus2_task_envclip_k16_train_to_test/data_hash.txt

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+{
+  "calibration_input": "d79e275b896eb98caa128470d4614b76960cab12407faa157c583224be7abe80",
+  "calibration_target_index": "67973c50072aa87a3b97533b6292b08a8b4d88a95571dc22e91b6e8fd19e0d85",
+  "eval_input": "541d5a928da5f7ee04ca3dea570e04208830dffde431edfe5b5e38b692634045",
+  "eval_target_index": "dee1b5225485df6624747dd4c5074bcf514685b54017d05e698d2051638fbf36",
+  "source_index": "67973c50072aa87a3b97533b6292b08a8b4d88a95571dc22e91b6e8fd19e0d85"
+}

runs/ctt_base_context_obs_learned_dominance_score_chartcompat_successbonus2_task_envclip_k16_train_to_test/eval.log

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+evaluated learned fallback rule on held-out measured rollout rows
+eval_input=runs/ctt_base_context_obs_test_envclip_k16_rollout_comparison/combined_measured_candidates.json
+num_eval_rows=144

runs/ctt_base_context_obs_learned_dominance_score_chartcompat_successbonus2_task_envclip_k16_train_to_test/git_hash.txt

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+14e81292e2004925f81e0bb4810f6f144bfd87b7

runs/ctt_base_context_obs_learned_dominance_score_chartcompat_successbonus2_task_envclip_k16_train_to_test/metrics_by_task.json

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+{
+  "LiftPegUpright-v1": {
+    "base_success": 0.2,
+    "base_utility": 0.9498705387115478,
+    "coverage": 0.4666666666666667,
+    "execute_generated": 0.4666666666666667,
+    "fallback_rate": 0.5333333333333333,
+    "hidden_chart_oracle_success": 1.0,
+    "hidden_chart_oracle_utility": 2.0,
+    "outcome_ptr": 0.5333333333333333,
+    "pairwise_causal_calibration_accuracy": 0.5492625405285252,
+    "pairwise_causal_calibration_confidence": 0.5651094024103738,
+    "pairwise_causal_calibration_ece": 0.11881236057424142,
+    "pairwise_causal_calibration_pairs": 94.8,
+    "predicted_margin": 0.8862852359573267,
+    "proposal_oracle_success": 0.6,
+    "proposal_oracle_utility": 1.4122399787108104,
+    "selected_candidate_index": 5.333333333333333,
+    "selected_success": 0.3333333333333333,
+    "selected_success_gain_over_base": 0.13333333333333333,
+    "selected_utility": 1.088020184636116,
+    "selected_utility_gain_over_base": 0.1381496459245682,
+    "selector_regret": 0.3509542107582092,
+    "success_selector_gap": 0.26666666666666666,
+    "success_support_gap": 0.4,
+    "support_gap": 0.5877600212891897,
+    "tau": 0.87335466614541
+  },
+  "PickCube-v1": {
+    "base_success": 0.0,
+    "base_utility": 0.5839591026306152,
+    "coverage": 0.0,
+    "execute_generated": 0.0,
+    "fallback_rate": 1.0,
+    "hidden_chart_oracle_success": 1.0,
+    "hidden_chart_oracle_utility": 2.0,
+    "outcome_ptr": 0.0,
+    "pairwise_causal_calibration_accuracy": 0.5277777777777778,
+    "pairwise_causal_calibration_confidence": 0.5553133321393634,
+    "pairwise_causal_calibration_ece": 0.10657979977343184,
+    "pairwise_causal_calibration_pairs": 36.0,
+    "predicted_margin": 0.5842980964012888,
+    "proposal_oracle_success": 0.0,
+    "proposal_oracle_utility": 0.13425676027933756,
+    "selected_candidate_index": 7.333333333333333,
+    "selected_success": 0.0,
+    "selected_success_gain_over_base": 0.0,
+    "selected_utility": 0.5839591026306152,
+    "selected_utility_gain_over_base": 0.0,
+    "selector_regret": 0.0,
+    "success_selector_gap": 0.0,
+    "success_support_gap": 1.0,
+    "support_gap": 1.8657432397206624,
+    "tau": 1.2894892762347252
+  },
+  "PullCube-v1": {
+    "base_success": 0.36,
+    "base_utility": 0.7751704612234608,
+    "coverage": 0.6533333333333333,
+    "execute_generated": 0.6533333333333333,
+    "fallback_rate": 0.3466666666666667,
+    "hidden_chart_oracle_success": 0.52,
+    "hidden_chart_oracle_utility": 1.1467878860235214,
+    "outcome_ptr": 0.4666666666666667,
+    "pairwise_causal_calibration_accuracy": 0.5216143238307843,
+    "pairwise_causal_calibration_confidence": 0.5584521161129652,
+    "pairwise_causal_calibration_ece": 0.13244853449538532,
+    "pairwise_causal_calibration_pairs": 92.32,
+    "predicted_margin": 0.6759761060180944,
+    "proposal_oracle_success": 0.5333333333333333,
+    "proposal_oracle_utility": 1.1093241602430741,
+    "selected_candidate_index": 5.986666666666666,
+    "selected_success": 0.29333333333333333,
+    "selected_success_gain_over_base": -0.06666666666666667,
+    "selected_utility": 0.6341658942727372,
+    "selected_utility_gain_over_base": -0.14100456695072353,
+    "selector_regret": 0.4787018513850247,
+    "success_selector_gap": 0.24,
+    "success_support_gap": 0.02666666666666667,
+    "support_gap": 0.1075624164690574,
+    "tau": 0.5825884328057477
+  },
+  "PushCube-v1": {
+    "base_success": 0.16666666666666666,
+    "base_utility": 0.3924041787783305,
+    "coverage": 0.7777777777777778,
+    "execute_generated": 0.7777777777777778,
+    "fallback_rate": 0.2222222222222222,
+    "hidden_chart_oracle_success": 0.8333333333333334,
+    "hidden_chart_oracle_utility": 1.7015800600250561,
+    "outcome_ptr": 0.8333333333333334,
+    "pairwise_causal_calibration_accuracy": 0.5465423944585421,
+    "pairwise_causal_calibration_confidence": 0.5419772241344875,
+    "pairwise_causal_calibration_ece": 0.11799694975778399,
+    "pairwise_causal_calibration_pairs": 97.44444444444444,
+    "predicted_margin": 1.3829754161601442,
+    "proposal_oracle_success": 0.8888888888888888,
+    "proposal_oracle_utility": 1.7857814149724112,
+    "selected_candidate_index": 3.7222222222222223,
+    "selected_success": 0.5555555555555556,
+    "selected_success_gain_over_base": 0.3888888888888889,
+    "selected_utility": 1.162042656706439,
+    "selected_utility_gain_over_base": 0.7696384779281087,
+    "selector_regret": 0.6237387582659721,
+    "success_selector_gap": 0.3333333333333333,
+    "success_support_gap": 0.1111111111111111,
+    "support_gap": 0.21421858502758873,
+    "tau": 0.8468573198810989
+  },
+  "StackCube-v1": {
+    "base_success": 0.2727272727272727,
+    "base_utility": 0.7763947045261209,
+    "coverage": 0.2727272727272727,
+    "execute_generated": 0.2727272727272727,
+    "fallback_rate": 0.7272727272727273,
+    "hidden_chart_oracle_success": 1.0,
+    "hidden_chart_oracle_utility": 2.0,
+    "outcome_ptr": 0.6363636363636364,
+    "pairwise_causal_calibration_accuracy": 0.5043423274143793,
+    "pairwise_causal_calibration_confidence": 0.5567990222574275,
+    "pairwise_causal_calibration_ece": 0.13094581844275163,
+    "pairwise_causal_calibration_pairs": 67.45454545454545,
+    "predicted_margin": 0.7229237046506615,
+    "proposal_oracle_success": 0.5151515151515151,
+    "proposal_oracle_utility": 1.1567951707225856,
+    "selected_candidate_index": 5.393939393939394,
+    "selected_success": 0.2727272727272727,
+    "selected_success_gain_over_base": 0.0,
+    "selected_utility": 0.7495684027671814,
+    "selected_utility_gain_over_base": -0.02682630175893957,
+    "selector_regret": 0.41081975310137775,
+    "success_selector_gap": 0.24242424242424243,
+    "success_support_gap": 0.48484848484848486,
+    "support_gap": 0.8432048292774142,
+    "tau": 1.0718654827809493
+  }
+}

runs/ctt_base_context_obs_learned_dominance_score_chartcompat_successbonus2_task_envclip_k16_train_to_test/split_hash.txt

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+{
+  "calibration_target_index": {
+    "content_hash": "67f7b4a692f7c7e71da24378dc71e3399c5d35afc14c494869eba6087b765c42",
+    "retrieval_index_allowed": true,
+    "split": "train",
+    "split_hash": "867a94a1c67686c082765671a7bf8d74a9d633085e1b2619c83197c60bf58372"
+  },
+  "eval_target_index": {
+    "content_hash": "0c38d73dc9bc4ab756e12006671b5d12f1a23358b281e54b3f6a9ae3cbf6e9af",
+    "retrieval_index_allowed": false,
+    "split": "test",
+    "split_hash": "84151df9e88c219b76751677558cc5bbbc19082bf358cea7330158e9e403e25f"
+  }
+}

runs/ctt_base_context_obs_learned_dominance_score_chartcompat_successbonus2_task_envclip_k16_train_to_test/table.tex

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+% Auto-generated by scripts/eval_learned_dominance_selector.py
+\begin{tabular}{lrrrrrrrrr}
+\toprule
+Rows & Coverage & Fallback & Base succ. & Selected succ. & Oracle succ. & OutcomePTR & Succ. support gap & Succ. selector gap & Cal. ECE \\
+\midrule
+144 & 0.5486 & 0.4514 & 0.2917 & 0.3194 & 0.5694 & 0.5486 & 0.2014 & 0.2500 & 0.0302 \\
+\bottomrule
+\end{tabular}

runs/ctt_base_context_obs_learned_dominance_score_chartcompat_successbonus2_task_envclip_k16_train_to_test/train.log

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+trained ridge dominance calibrator on calibration measured rows only
+fit_objective=pointwise
+selected_lambda=10.0
+tau={"LiftPegUpright-v1": 0.873355, "PickCube-v1": 1.289489, "PullCube-v1": 0.582588, "PushCube-v1": 0.846857, "StackCube-v1": 1.071865, "__global__": 0.933426}
+calibration_input=runs/ctt_base_context_obs_train_cal_envclip_k16_rollout_comparison/combined_measured_candidates.json