{"id":"W3134342065","doi":"10.1002/sim.8922","title":"uTPI: A utility‐based toxicity probability interval design for phase I/II dose‐finding trials","year":2021,"lang":"en","type":"article","venue":"Statistics in Medicine","topic":"Statistical Methods in Clinical Trials","field":"Mathematics","cited_by":23,"is_retracted":false,"has_abstract":true,"ca_institutions":"Simon Fraser University","funders":"National Cancer Institute; National Institutes of Health","keywords":"Maximum tolerated dose; Confidence interval; Clinical trial; Toxicity; Parametric statistics; Computer science; Medicine; Clinical study design; Optimal design; Interval (graph theory); Statistics; Mathematics; Machine learning; Internal medicine","routes":{"ca_aff":true,"ca_fund":false,"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":[],"consensus_categories":[],"category_scores_codex":[0.04022588,0.001850285,0.00210598,0.001454856,0.0004411156,0.001596666,0.002681835,0.001829158,0.004297482],"category_scores_gemma":[0.06023899,0.001018945,0.001475085,0.001286527,0.001778797,0.001589244,0.00226217,0.003359595,0.0005396985],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001218447,"about_ca_system_score_gemma":0.002505935,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004786412,"about_ca_topic_score_gemma":0.0003774517,"domain_scores_codex":[0.9683877,0.02718376,0.0008452433,0.001503526,0.001630589,0.0004491852],"domain_scores_gemma":[0.9698924,0.0231372,0.002738795,0.001813218,0.001593855,0.0008245137],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0100189,0.0007536415,0.004411485,0.001328009,0.0005832065,0.0004277604,0.000394731,0.5434453,0.007575958,0.1788849,0.003300232,0.2488759],"study_design_scores_gemma":[0.002284398,0.003967084,0.0009573036,0.0001147875,0.0002345402,0.0001695772,0.00003098835,0.9128369,0.003320426,0.07212123,0.00387901,0.0000836562],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.008210474,0.0003299044,0.9882675,0.0001645354,0.00006137216,0.001723647,0.0001199063,0.0002590329,0.0008636096],"genre_scores_gemma":[0.3442861,0.0005392196,0.642081,0.0005192032,0.00009815226,0.01053101,0.0003468391,0.0001010651,0.001497454],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.04022588,"threshold_uncertainty_score":0.2127373,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.8161295342178478,"score_gpt":0.6464013638722923,"score_spread":0.1697281703455555,"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."}}