{"id":"W4413114376","doi":"10.1002/pst.70037","title":"Drift Parameter Based Sample Size Determination in Multi‐Stage Bayesian Randomized Clinical Trials","year":2025,"lang":"en","type":"article","venue":"Pharmaceutical Statistics","topic":"Statistical Methods in Clinical Trials","field":"Mathematics","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Simon Fraser University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Sample size determination; Bayesian probability; Statistics; Stage (stratigraphy); Randomized controlled trial; Clinical trial; Mathematics; Computer science; Econometrics; Medicine; Internal medicine; Biology","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":[0.07962111,0.001497649,0.003470918,0.002548344,0.0008022006,0.002255333,0.003635491,0.002813747,0.006650532],"category_scores_gemma":[0.2058854,0.001661845,0.001985164,0.002169108,0.00275225,0.003091221,0.003504581,0.004876919,0.00151823],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00205624,"about_ca_system_score_gemma":0.005884549,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001443851,"about_ca_topic_score_gemma":0.00146444,"domain_scores_codex":[0.9376535,0.05368411,0.001899735,0.002454597,0.003912707,0.0003953451],"domain_scores_gemma":[0.8727289,0.1133007,0.004746465,0.0051325,0.00330163,0.0007896898],"domain_codex":null,"domain_gemma":"methods","domain_candidate":"methods","domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.002293114,0.0002502596,0.004090948,0.002537093,0.0007193935,0.0002827234,0.000555667,0.1840179,0.003003249,0.2770216,0.01102415,0.514204],"study_design_scores_gemma":[0.001255343,0.000611838,0.0009812396,0.0005503463,0.0002331498,0.000231678,0.00004951803,0.6232255,0.003650516,0.3573058,0.01180497,0.0001000747],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.001400943,0.0005871975,0.9961665,0.0003296068,0.00006680856,0.000494583,0.00007870635,0.0003268999,0.0005487663],"genre_scores_gemma":[0.06602877,0.000778732,0.9272608,0.0006652146,0.000154293,0.003763846,0.0002370654,0.000324023,0.0007872712],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.9203789,"threshold_uncertainty_score":0.4210817,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.7611773147160606,"score_gpt":0.6919872169274078,"score_spread":0.06919009778865282,"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."}}