{"id":"W4244056413","doi":"10.1002/9781118445112.stat06402","title":"Test Construction","year":2014,"lang":"en","type":"other","venue":"Wiley StatsRef: Statistics Reference Online","topic":"Psychometric Methodologies and Testing","field":"Decision Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"","keywords":"Test (biology); Function (biology); Construct (python library); Computer science; Item bank; Computerized adaptive testing; Key (lock); Item response theory; Process (computing); Data mining; Information retrieval; Artificial intelligence; Statistics; Mathematics; Psychometrics; Programming language","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":[0.0160431,0.001918753,0.001385739,0.007407816,0.001918038,0.003736709,0.003549212,0.001383627,0.0931668],"category_scores_gemma":[0.09060798,0.0008714694,0.001721862,0.004888529,0.001406384,0.002477119,0.0055179,0.00315503,0.0437082],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002920223,"about_ca_system_score_gemma":0.008015349,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003236935,"about_ca_topic_score_gemma":0.002496176,"domain_scores_codex":[0.9862418,0.005424078,0.001483085,0.001502255,0.004651564,0.000697202],"domain_scores_gemma":[0.9613855,0.01167402,0.001282127,0.006245667,0.01783657,0.001576042],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0004869735,0.0007728944,0.01558466,0.001077672,0.00006868659,0.0004575592,0.001635503,0.002480781,0.00285554,0.03543109,0.1220581,0.8170906],"study_design_scores_gemma":[0.0006696553,0.002361793,0.04266744,0.002494094,0.0002891722,0.001453258,0.003367953,0.0184485,0.0206212,0.09534156,0.8120279,0.0002575304],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.0630635,0.001299369,0.5775934,0.003791357,0.002700979,0.05497279,0.04073371,0.01292701,0.2429179],"genre_scores_gemma":[0.1636247,0.001208561,0.6285224,0.002339384,0.000577994,0.05498878,0.06555567,0.00442266,0.07875991],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.0931668,"threshold_uncertainty_score":0.311674,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.353458140929248,"score_gpt":0.4677002338967999,"score_spread":0.1142420929675519,"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."}}