| { |
| "created_utc": "2026-11-09T14:38:24.151548+00:00", |
| "status": "Post-review exploratory analysis of already opened worlds; not confirmation", |
| "scientific_question": "Why does joint minus action-value utility shrink with sample size?", |
| "authorization": "User authorized additional reviewer-response experiments; no new approval requested.", |
| "source_release": "/home/nurgaly/experiment/unionmind/articles/make_1/release/huggingface-revised", |
| "code_sha256": "4a300dfc769473f5afb08e15e877f6c53dfff5f6d3a0abfe17e0043798eecbab", |
| "device": "cuda:4", |
| "input_sha256": { |
| "data/controlled/worlds.safetensors": "e8649aeaed970fa78c3f402bbe9e775c486f3cf94ce2494cfe98a8099dbf3c7c", |
| "data/controlled/worlds.json": "860e154c4ffd0690080ab8c263756d4340cc119fffa66e1cc41d1b42ac3848cb", |
| "data/controlled/manifest.json": "2b50155e7f4d198449e2499dad21ba82d51e94423a1711eca8de4a01ab9ca156", |
| "postconfirmation.py": "3365341c056cee9b153cc864bad864965c918e11e0cec1819d49c8875c68dcbf", |
| "unionmind/decision_sufficiency/core.py": "fa2f7405a8d0dc6ec96ebae1bb2a2b810d03ef1fd2877f5ebef7df1722992cee", |
| "results/postconfirmation/controlled_worlds.csv.gz": "bdb15095eadf96dff2aa316619a838b74024eece87c57143bcd44b4710e9547f", |
| "results/postconfirmation/controlled_frontiers.csv.gz": "946ebf8764ee3dfed5a741fa3a45e0cb5f8476960453716d9abebed0aa617e57", |
| "results/postconfirmation/controlled_timing.json": "082e8b981d9e6b13a07bfd3136d6afe08681bb8c702ba2c0c2b9a2d4966b6eea", |
| "provenance/controlled/confirmation_benchmark.json": "133420e45f42ff5dbacc8d01700aeba56bf65c02f5bc0b30bb7aff45a88bc249" |
| }, |
| "units": "All 192 archived worlds, all six families, all three original nested sample streams", |
| "grid": { |
| "availability": [ |
| 6, |
| 3 |
| ], |
| "records": [ |
| 64, |
| 256, |
| 1024, |
| 4096 |
| ], |
| "estimators": [ |
| "joint_jeffreys", |
| "naive_bayes", |
| "support_mixture" |
| ], |
| "methods": [ |
| "identity", |
| "query_joint", |
| "posterior_clusters", |
| "posterior_bins", |
| "future_marginal", |
| "raw_information", |
| "raw_entropy", |
| "hash_code", |
| "action_values" |
| ], |
| "budgets": [ |
| 0, |
| 1, |
| 2 |
| ], |
| "costs": [ |
| 0.0, |
| 0.01, |
| 0.05 |
| ] |
| }, |
| "primary_aggregation": "Average positive budgets, all costs and three streams within each world; equal worlds and six families", |
| "interventions": [ |
| "Native: estimated-law encoder, estimated encoded-law exact planner, true-law evaluation", |
| "Replan the identical native code under the pushed true law to separate encoding and model-estimation loss", |
| "Privileged diagnostic: construct each unchanged encoder under the true law, then plan under either true or fitted pushed law; never a deployable competitor" |
| ], |
| "exact_decomposition": "J-A = (encoding_loss_A-encoding_loss_J) + (estimation_loss_A-estimation_loss_J)", |
| "encoding_loss": "V(available true raw law)-V(true law pushed through native code)", |
| "estimation_loss": "V(true law pushed through native code)-realized utility of fitted policy", |
| "alias_diagnostic": "Evaluate all unordered raw-state pairs with true current-posterior difference <=1e-12 (exact) and <=0.01 (fixed near-alias threshold), weighted by 2 P(e)P(e'); compare true optimal root choices at each cost and budget and whether each native code merges disagreeing aliases", |
| "intervals": "Descriptive paired 95% percentile bootstrap, 10,000 draws, seed 18701, worlds resampled within fixed families after averaging streams; intervals are not corrected and are not new confirmatory tests", |
| "practical_scale": "Joint-action gain divided by remaining true available-oracle headroom of action-values; report signed gain, not just a percentage", |
| "timing": "Retain published complete-cost records. Fresh warm alternating-order 11-repeat 192-world primary-batch timings include count/estimate, profile, clustering/other encoding, push, exact planning, materialization and 1/32/1024/65536 recorded-event replays. One warmup charged and separately reported. Timing is descriptive on shared hardware.", |
| "prohibition": "No tuning, no model refits, no changed codes/iterations/costs, no dropped units, no original results or manuscript edits, no promotion", |
| "planned_outputs": [ |
| "scores.npz", |
| "indices.json", |
| "frontier_all_conditions.csv", |
| "paired_by_condition.csv", |
| "sample_frontier.csv", |
| "family_sample_frontier.csv", |
| "native_worlds.csv.gz", |
| "alias_pairs.csv.gz", |
| "alias_summary.csv", |
| "privileged_geometry.csv", |
| "timing.json", |
| "summary.json", |
| "compute.json" |
| ], |
| "amendment_01": { |
| "created_utc": "2026-11-09T14:43:15.749761+00:00", |
| "reason": "The expanded execution trace completed and saved all grid cells, then strict whole-grid native replay validation failed. 946/124416 archived world means differ; primary-mixture joint/action-value/identity at all sample sizes match within 3.34e-16. Preserve all discrepancies and original code/spec/log; aggregate fresh diagnostics without altering source results. Run the released original full grid as a separate trace comparison to investigate tie/numerical sensitivity.", |
| "previous_code_sha256": "db7360ee28143a5b9f1e16f373d887354f4824826d8d9b5ed64425e6b732a5dc", |
| "completed_grid_code": "collection_code_01.py", |
| "completed_grid_specification": "specification_01.json", |
| "analysis_changes": "Validation/reporting repair only; no new encoders, thresholds, unit exclusions, tuning, or changed data. Add --resume-aggregation and --reference-only. All native values/oracles in each decomposition come from the same execution trace." |
| }, |
| "amendment_02": { |
| "created_utc": "2026-11-09T14:47:08.492706+00:00", |
| "reason": "The unmodified released full-grid controlled replay also differs from archive in 968/124416 native world means while exactly reproducing the headline frontier. Test finite-precision argmax sensitivity directly.", |
| "operation": "For all grid cells and fixed freshly constructed encoders, compare normal pushforward to accumulation over reversed raw-state order. This is mathematically the same law; measure maximum cell-law perturbation, fitted-optimal expected-value difference, and true-law realized-utility difference.", |
| "no_scientific_comparator_change": true, |
| "new_outputs": [ |
| "numeric_push_sensitivity.npz", |
| "numeric_push_sensitivity.csv.gz", |
| "numeric_diagnostic.json", |
| "numeric_compute.json" |
| ] |
| } |
| } |
|
|
