{"id":"W3112823139","doi":"10.3390/psych2040026","title":"Better Rating Scale Scores with Information–Based Psychometrics","year":2020,"lang":"en","type":"article","venue":"Psych","topic":"Psychometric Methodologies and Testing","field":"Decision Sciences","cited_by":11,"is_retracted":false,"has_abstract":true,"ca_institutions":"Ottawa Hospital; McGill University","funders":"","keywords":"Metric (unit); A priori and a posteriori; Psychometrics; Scale (ratio); Computer science; Item response theory; Rating scale; Data science; Statistics; Test (biology); Data mining; Econometrics; Psychology; Machine learning; Mathematics","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"],"consensus_categories":[],"category_scores_codex":[0.002882933,0.0001658102,0.0003225479,0.0006574952,0.0002268098,0.001033975,0.001563362,0.0000672381,0.0005444611],"category_scores_gemma":[0.03229691,0.0001063869,0.00007030194,0.00918785,0.00007539723,0.0009519533,0.0001543872,0.0002268233,0.0004206623],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001359221,"about_ca_system_score_gemma":0.00006075424,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001613171,"about_ca_topic_score_gemma":0.000003414214,"domain_scores_codex":[0.9969614,0.0002102525,0.0007204629,0.0004311845,0.001356081,0.0003206353],"domain_scores_gemma":[0.9901405,0.008209491,0.0004589353,0.0005753701,0.0003860003,0.000229712],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001321882,0.00004022844,0.5571324,0.00001715549,0.00001410262,0.000002215299,0.0005478618,0.000399204,0.000053761,0.0001625121,0.06806613,0.3734322],"study_design_scores_gemma":[0.005823585,0.001477299,0.6050748,0.0001052592,0.00004662732,0.00002190084,0.00270933,0.04717113,0.001298573,0.01587806,0.3191792,0.00121422],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2448566,0.0001432056,0.6688836,0.01945445,0.0007110815,0.0004622875,0.00002237049,0.000186622,0.06527986],"genre_scores_gemma":[0.6467254,0.000003426823,0.3376987,0.01529105,0.0001800543,0.00002156668,0.000005554328,0.00001192356,0.00006227969],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.4018688,"threshold_uncertainty_score":0.9970649,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.4308961238263982,"score_gpt":0.4354774462568831,"score_spread":0.004581322430484869,"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."}}