{"id":"W2071849850","doi":"10.3102/1076998609332756","title":"Sample Size Estimation in Cluster Randomized Educational Trials: An Empirical Bayes Approach","year":2009,"lang":"en","type":"article","venue":"Journal of Educational and Behavioral Statistics","topic":"Statistical Methods and Bayesian Inference","field":"Mathematics","cited_by":30,"is_retracted":false,"has_abstract":true,"ca_institutions":"Western University","funders":"","keywords":"Intraclass correlation; Bayes' theorem; Computer science; Cluster (spacecraft); Statistics; Sample size determination; Estimation; Sample (material); Data mining; Task (project management); Field (mathematics); Econometrics; Bayesian probability; Mathematics; Artificial intelligence; Psychometrics","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":[0.2323861,0.002486333,0.00945213,0.005913597,0.00135379,0.003259601,0.006612604,0.005829132,0.004191216],"category_scores_gemma":[0.4642672,0.002101685,0.004328791,0.004186567,0.004222088,0.003808479,0.003097125,0.007025414,0.0008724232],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002558714,"about_ca_system_score_gemma":0.005226885,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002765544,"about_ca_topic_score_gemma":0.002156398,"domain_scores_codex":[0.7071114,0.2725939,0.006104433,0.006005429,0.007532097,0.0006527388],"domain_scores_gemma":[0.4853451,0.490923,0.006569588,0.01156225,0.004773323,0.0008268286],"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":[0.005051261,0.0006249609,0.005051394,0.00515365,0.005032888,0.0004529592,0.001352862,0.2081111,0.0008937987,0.3569687,0.01241947,0.3988869],"study_design_scores_gemma":[0.002102643,0.0008913616,0.0009486942,0.001359178,0.001013326,0.000236837,0.00008255611,0.4869437,0.001020999,0.4999085,0.00534665,0.0001456389],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.001327778,0.0007799871,0.9954199,0.0004957307,0.0001089878,0.001274565,0.0000641786,0.0001848704,0.0003439629],"genre_scores_gemma":[0.04678622,0.000776261,0.9432451,0.0006357772,0.0002367469,0.007687544,0.0001563687,0.00009665392,0.0003793122],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.7676139,"threshold_uncertainty_score":0.9466045,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1729810713784575,"score_gpt":0.5008700679701498,"score_spread":0.3278889965916923,"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."}}