{"id":"W4284899235","doi":"10.1002/sta4.487","title":"Bayesian group sequential designs for cluster‐randomized trials","year":2022,"lang":"en","type":"article","venue":"Stat","topic":"Statistical Methods in Clinical Trials","field":"Mathematics","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"Mitacs","keywords":"Randomized controlled trial; Cluster (spacecraft); Sample size determination; Interim; Cluster randomised controlled trial; Bayesian probability; Computer science; Statistics; Psychology; Medicine; Artificial intelligence; Mathematics; Surgery; Geography","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":[0.1984309,0.003605857,0.005377749,0.004018989,0.001337318,0.004030085,0.005524563,0.005221956,0.01884157],"category_scores_gemma":[0.2982757,0.002478981,0.004939668,0.004508472,0.004840616,0.004814102,0.003794547,0.008741532,0.003780469],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003866951,"about_ca_system_score_gemma":0.008295598,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00157664,"about_ca_topic_score_gemma":0.001900397,"domain_scores_codex":[0.7624646,0.2179708,0.004345452,0.004993705,0.009073234,0.001152134],"domain_scores_gemma":[0.7481956,0.2098691,0.01343082,0.0149834,0.01142909,0.002092043],"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":[0.002532562,0.0002787913,0.001448077,0.002456903,0.001218734,0.0001710347,0.000784085,0.1248388,0.0005824558,0.7460762,0.01262785,0.1069845],"study_design_scores_gemma":[0.003911012,0.00140704,0.0005676557,0.0008819403,0.0004211095,0.0001213611,0.00009504426,0.3701819,0.0008698456,0.6053609,0.01601151,0.0001706967],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.0008115761,0.0004559253,0.9946893,0.0004718757,0.0002659201,0.002075621,0.0001700273,0.0002919564,0.000767816],"genre_scores_gemma":[0.03860257,0.001041446,0.9395964,0.0008401968,0.0003032536,0.01779033,0.0004118125,0.0001536813,0.001260393],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.1984309,"threshold_uncertainty_score":0.9884773,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.7519692633517723,"score_gpt":0.6057972438282709,"score_spread":0.1461720195235013,"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."}}