{"id":"W2140217706","doi":"10.1348/000711003321645412","title":"Pairwise multiple comparisons: A model comparison approach versus stepwise procedures","year":2003,"lang":"en","type":"article","venue":"British Journal of Mathematical and Statistical Psychology","topic":"Optimal Experimental Design Methods","field":"Decision Sciences","cited_by":28,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Manitoba; York University","funders":"","keywords":"Pairwise comparison; Selection (genetic algorithm); Normality; Model selection; Multiple comparisons problem; Set (abstract data type); Variance (accounting); Mathematics; Statistics; Type I and type II errors; Computer science; Econometrics; Machine learning","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":[],"consensus_categories":[],"category_scores_codex":[0.166623,0.004191684,0.005051565,0.004951563,0.001600414,0.002578388,0.007465878,0.003272175,0.008000341],"category_scores_gemma":[0.351334,0.001497655,0.005308397,0.006982219,0.005506323,0.006119796,0.004459914,0.009498944,0.000989716],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001467537,"about_ca_system_score_gemma":0.003734224,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0006687517,"about_ca_topic_score_gemma":0.001046619,"domain_scores_codex":[0.738834,0.2289693,0.006957502,0.01150342,0.01242369,0.001311978],"domain_scores_gemma":[0.6395472,0.3136663,0.01378063,0.02527624,0.006374178,0.001355487],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.007816106,0.002526748,0.008332752,0.01017028,0.01572323,0.001331616,0.005784046,0.06175049,0.01329186,0.2510722,0.0195241,0.6026767],"study_design_scores_gemma":[0.002575243,0.02323871,0.00987979,0.001619539,0.002913887,0.001212804,0.001243224,0.3451964,0.01627809,0.5672421,0.02788601,0.000714209],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.01026941,0.0004018651,0.9839436,0.0005578181,0.0004892607,0.002622616,0.0002384526,0.0006039778,0.0008730654],"genre_scores_gemma":[0.05799088,0.0003585846,0.9319915,0.0002666872,0.0001651354,0.00842938,0.0001482284,0.0002023561,0.000447343],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.166623,"threshold_uncertainty_score":0.8811974,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2715206547783738,"score_gpt":0.4866960714425734,"score_spread":0.2151754166641996,"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."}}