{"id":"W1736389262","doi":"10.1002/0470013192.bsa420","title":"Multiple Comparison Procedures","year":2005,"lang":"en","type":"other","venue":"Encyclopedia of Statistics in Behavioral Science","topic":"Statistical Methods in Clinical Trials","field":"Mathematics","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"York University; University of Manitoba","funders":"","keywords":"Pairwise comparison; Variance (accounting); Homogeneity (statistics); Statistics; Analysis of variance; Normality; Multiple comparisons problem; Mathematics; Simple (philosophy); Variance components; Computer science; Econometrics","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":"codex-gemma-dda1882f352a","candidate_categories":["metaresearch","metaepi_narrow","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.002154943,0.0004179236,0.001273219,0.0005446664,0.00005902956,0.00003617278,0.001190628,0.0003711862,0.002847996],"category_scores_gemma":[0.04975908,0.0003838389,0.00007243075,0.0008306599,0.001966957,0.00006913376,0.0002893975,0.0006143512,0.00005360429],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001607086,"about_ca_system_score_gemma":0.0005870588,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004876231,"about_ca_topic_score_gemma":0.002669164,"domain_scores_codex":[0.9953458,0.0002110752,0.001590076,0.0008025909,0.001399736,0.0006507662],"domain_scores_gemma":[0.9895539,0.008238949,0.001084199,0.0007117303,0.000166101,0.0002451464],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.00007332274,0.00316644,0.04118898,0.0009981191,0.00002010724,0.00007207987,0.0007183857,0.000007022379,0.0001322562,0.1288818,0.6451008,0.1796407],"study_design_scores_gemma":[0.004395514,0.001230092,0.02505945,0.003816537,0.0006833976,0.00001204123,0.0004489872,0.001205105,0.0005042876,0.7282357,0.2309036,0.003505345],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"other","genre_gemma":"methods","genre_scores_codex":[0.001339521,0.0003431769,0.140732,0.00004798536,0.003612481,0.002740373,0.005136548,0.0003610463,0.8456869],"genre_scores_gemma":[0.001729273,0.0003543864,0.9320994,0.00001287117,0.0003298266,0.00006152257,0.000008630746,0.0002417374,0.06516235],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.7913674,"threshold_uncertainty_score":0.9998614,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.3089900183529948,"score_gpt":0.5481415482586365,"score_spread":0.2391515299056417,"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."}}