{"id":"W4399135167","doi":"10.1002/sim.10116","title":"Structured learning in time‐dependent Cox models","year":2024,"lang":"en","type":"article","venue":"Statistics in Medicine","topic":"Neural Networks and Applications","field":"Computer Science","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Montréal; McGill University; Mila - Quebec Artificial Intelligence Institute","funders":"Fonds de recherche du Québec – Nature et technologies; Fonds de Recherche du Québec - Santé; Canadian Institutes of Health Research; Ministère de la Santé et des Services sociaux; Réseau Québécois de Recherche sur les Médicaments; Natural Sciences and Engineering Research Council of Canada; Heart and Stroke Foundation of Canada","keywords":"Computer science; Proportional hazards model; Econometrics; Statistics; Mathematics","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002948637,0.000078319,0.0001296781,0.0001188602,0.00002833363,0.0000438735,0.0003170325,0.00002959013,0.00005428755],"category_scores_gemma":[0.00004007136,0.00006330832,0.000006622709,0.0004188929,0.00004308179,0.00008276066,0.0000802115,0.000319513,0.00002426502],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003941455,"about_ca_system_score_gemma":0.00003145374,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00006357319,"about_ca_topic_score_gemma":0.00006425323,"domain_scores_codex":[0.9990909,0.00004133902,0.0002126066,0.0002453973,0.0002437694,0.0001660041],"domain_scores_gemma":[0.9994766,0.0002690841,0.00002240036,0.000168497,0.0000184448,0.00004501914],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.000003306867,0.00001735073,0.0001971886,0.00003933752,0.000006030394,0.0002942343,0.001333388,0.06372786,0.000645333,0.8079447,0.01328136,0.1125099],"study_design_scores_gemma":[0.000145381,0.00003180337,0.000372838,0.00008766844,0.00000209183,0.000007160937,0.00001313409,0.7882533,0.00001284655,0.2095769,0.001439348,0.00005750764],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.001534928,0.0004682048,0.9946505,0.001606724,0.0002362585,0.0001191508,0.000008646045,0.00008063784,0.001294933],"genre_scores_gemma":[0.9535031,0.0001611558,0.04452063,0.0002578862,0.000132864,0.00001949544,0.00002368337,0.00001038105,0.001370806],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.9519682,"threshold_uncertainty_score":0.2581638,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01719439439714924,"score_gpt":0.3004267088436853,"score_spread":0.283232314446536,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}