{"id":"W7117654090","doi":"10.6084/m9.figshare.30969710","title":"Additional file 3 of Who benefits? Uncovering hidden heterogeneity of treatment effects in adaptive trials using Bayesian methods: a systematic review","year":2025,"lang":"","type":"article","venue":"Figshare","topic":"Statistical Methods in Clinical Trials","field":"Mathematics","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University Health Network; SickKids Foundation; Hospital for Sick Children; University of Toronto","funders":"","keywords":"Bayesian probability; Bayesian inference; Bayesian statistics; Key (lock); Statistical model","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":["metaresearch","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.008190617,0.0019517,0.003588104,0.005595255,0.0007250644,0.002782402,0.002466065,0.002101486,0.8656338],"category_scores_gemma":[0.1286314,0.001350429,0.004660015,0.009326811,0.0004754469,0.004012711,0.001891229,0.001550123,0.05349595],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002525381,"about_ca_system_score_gemma":0.005366975,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005836675,"about_ca_topic_score_gemma":0.0141878,"domain_scores_codex":[0.9960732,0.001256347,0.001228961,0.0005176124,0.0006240633,0.000299724],"domain_scores_gemma":[0.8738126,0.1083558,0.008972136,0.002366921,0.005699041,0.0007933619],"domain_codex":null,"domain_gemma":"methods","domain_candidate":"methods","domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"systematic_review","study_design_scores_codex":[0.002063991,0.00008605995,0.002022542,0.3650532,0.001578344,0.0001917996,0.0002536823,0.001576274,0.0002550232,0.004706926,0.5971521,0.02506002],"study_design_scores_gemma":[0.05149354,0.001011331,0.02451059,0.2043476,0.01057425,0.001120894,0.0007143721,0.007316472,0.001322663,0.05153469,0.6454514,0.0006022654],"study_design_candidate":"systematic_review","study_design_consensus":null,"genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0002875798,0.000657638,0.0009719299,0.0005065125,0.00009843232,0.001863115,0.9935433,0.0004382896,0.001633224],"genre_scores_gemma":[0.03679902,0.005675891,0.04620015,0.007068161,0.0007391424,0.1208439,0.7337134,0.002585697,0.04637474],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.9918094,"threshold_uncertainty_score":0.1916571,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.5519478193213218,"score_gpt":0.5565899054538088,"score_spread":0.004642086132487067,"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."}}