{"id":"W2313243722","doi":"10.1177/1740774516634316","title":"Substantial risks associated with few clusters in cluster randomized and stepped wedge designs","year":2016,"lang":"en","type":"article","venue":"Clinical Trials","topic":"Statistical Methods in Clinical Trials","field":"Mathematics","cited_by":97,"is_retracted":false,"has_abstract":true,"ca_institutions":"Women's College Hospital; University of Toronto; Ottawa Hospital; University of Ottawa","funders":"","keywords":"Generalizability theory; Sample size determination; Cluster (spacecraft); Statistics; Statistical power; Computer science; Research design; Wedge (geometry); Type I and type II errors; Correlation; Cluster size; Contrast (vision); Econometrics; Mathematics; Artificial intelligence","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"],"consensus_categories":["metaresearch"],"category_scores_codex":[0.4613425,0.002454346,0.006093151,0.002373519,0.002697266,0.003759607,0.00552647,0.006380526,0.009306077],"category_scores_gemma":[0.6319046,0.002679793,0.004841036,0.003176303,0.0106865,0.006446165,0.006642777,0.009869822,0.001556881],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.004970247,"about_ca_system_score_gemma":0.009855643,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001835427,"about_ca_topic_score_gemma":0.00299195,"domain_scores_codex":[0.3677678,0.5630437,0.0212765,0.01645754,0.02960537,0.001849112],"domain_scores_gemma":[0.2656573,0.6172343,0.03404902,0.07095452,0.009826749,0.002278133],"domain_codex":"methods","domain_gemma":"methods","domain_candidate":"methods","domain_consensus":"methods","study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.02496036,0.001486965,0.01342279,0.008310236,0.006389779,0.0007954051,0.006880599,0.03354537,0.001496636,0.5884445,0.01652853,0.2977389],"study_design_scores_gemma":[0.01130742,0.00871394,0.008953976,0.004763157,0.002409338,0.0008499246,0.001012929,0.09869453,0.00426124,0.8260272,0.03251121,0.0004952479],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.02307656,0.003379018,0.9452388,0.005748314,0.001105074,0.01504451,0.0004056506,0.0005727613,0.005429292],"genre_scores_gemma":[0.2305997,0.0009639408,0.7117276,0.004876663,0.0003025005,0.04867719,0.0002416824,0.0001968158,0.002413904],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.5386574,"threshold_uncertainty_score":0.6642605,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.8556771333791159,"score_gpt":0.6453227649648124,"score_spread":0.2103543684143034,"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."}}