{"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":"codex-gemma-dda1882f352a","candidate_categories":["metaresearch","insufficient_payload"],"consensus_categories":["metaresearch"],"category_scores_codex":[0.05353413,0.0002290892,0.00230122,0.000091542,0.0003230545,0.00006024443,0.0003636112,0.00009367293,0.003502973],"category_scores_gemma":[0.3462178,0.0001862787,0.0008863317,0.0001694865,0.000182011,0.00004685435,0.0002250269,0.0002968138,0.00001120167],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001155791,"about_ca_system_score_gemma":0.00008535892,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001192557,"about_ca_topic_score_gemma":0.000004363086,"domain_scores_codex":[0.9809944,0.01527703,0.002205442,0.0004799016,0.0005760385,0.0004672086],"domain_scores_gemma":[0.6858251,0.3129466,0.0006301961,0.0003928237,0.00006946387,0.0001357504],"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":[0.1262303,0.0004408925,0.000003728498,0.0002529889,0.0006556351,0.00001707784,0.0004114885,0.00003790159,0.0007158461,0.7835327,0.06347994,0.02422157],"study_design_scores_gemma":[0.1057654,0.0003037399,3.520232e-7,0.00001236945,0.0005015968,0.000004238676,0.0001077154,0.002986036,0.0002729807,0.8861315,0.003707272,0.0002068715],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.0003895056,0.00004146993,0.9898792,0.0007031245,0.002344681,0.004564044,0.0009540534,0.0001375886,0.0009863342],"genre_scores_gemma":[0.01193476,0.00001035355,0.983613,0.0005961732,0.0006229323,0.002344666,0.00002171012,0.00007241133,0.0007840443],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.2976696,"threshold_uncertainty_score":0.997408,"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."}}