{"id":"W4413048133","doi":"10.1002/sim.70215","title":"Health Utility Survival for Randomized Clinical Trials: Extensions and Statistical Properties","year":2025,"lang":"en","type":"article","venue":"Statistics in Medicine","topic":"Health Systems, Economic Evaluations, Quality of Life","field":"Economics, Econometrics and Finance","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Princess Margaret Cancer Centre; Public Health Ontario; University of Toronto; University Health Network","funders":"Fundamental Research Funds for the Central Universities; National Natural Science Foundation of China; Princess Margaret Cancer Foundation","keywords":"Clinical endpoint; Sample size determination; Statistics; Survival analysis; Randomized controlled trial; Medicine; Clinical trial; Statistical hypothesis testing; Statistical power; Econometrics; Computer science; Mathematics; Surgery; Internal medicine","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.4925276,0.004056591,0.006760479,0.006613451,0.0008837289,0.00665315,0.004370161,0.005987793,0.008738364],"category_scores_gemma":[0.6532767,0.002222484,0.007849243,0.008614448,0.007034961,0.01020622,0.006351323,0.01200108,0.001822583],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003573622,"about_ca_system_score_gemma":0.005425144,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001149162,"about_ca_topic_score_gemma":0.0007359915,"domain_scores_codex":[0.5703445,0.4014794,0.01017424,0.006952807,0.00991396,0.001135098],"domain_scores_gemma":[0.268223,0.6730747,0.02057427,0.02799864,0.008929223,0.001200217],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.004284338,0.0002987136,0.01366881,0.00798706,0.006838558,0.0008020029,0.00159031,0.1210286,0.0005405668,0.5897191,0.01030355,0.2429385],"study_design_scores_gemma":[0.001642656,0.001597312,0.002566715,0.002505896,0.001557948,0.0007363499,0.0001576247,0.3804935,0.0005871429,0.5919716,0.01601195,0.0001712309],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.00457192,0.005548461,0.9795299,0.002755158,0.0004262185,0.003727717,0.0005251312,0.0005972788,0.002318205],"genre_scores_gemma":[0.1710662,0.005993315,0.7918284,0.003060899,0.0009707546,0.023303,0.001203161,0.0004544046,0.002119973],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.4925276,"threshold_uncertainty_score":0.6258038,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.6863747557470252,"score_gpt":0.6045958885801116,"score_spread":0.08177886716691363,"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."}}