{"id":"W2619991132","doi":"10.1007/978-3-319-56129-5_5","title":"Putting Flesh on the Psychometric Bone: Making Sense of IRT Parameters in Non-cognitive Measures by Investigating the Social-Cognitive Aspects of the Items","year":2017,"lang":"en","type":"book-chapter","venue":"Social indicators research series","topic":"Psychometric Methodologies and Testing","field":"Decision Sciences","cited_by":4,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of British Columbia","funders":"","keywords":"Psychology; Item response theory; Cognition; CLARITY; Cognitive psychology; Scale (ratio); Sample (material); Developmental psychology; Psychometrics; Social psychology","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","sts","research_integrity"],"consensus_categories":["metaresearch","sts"],"category_scores_codex":[0.03841544,0.000542029,0.001299094,0.002884652,0.003965729,0.0006266488,0.002826679,0.0006905676,0.00005718191],"category_scores_gemma":[0.2824906,0.0002876679,0.0006377299,0.00439164,0.00839141,0.0002660314,0.001203499,0.003440196,0.00001711643],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001972177,"about_ca_system_score_gemma":0.0006822602,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003077698,"about_ca_topic_score_gemma":0.0001749666,"domain_scores_codex":[0.9855174,0.004105674,0.001692132,0.001053575,0.006628136,0.001003073],"domain_scores_gemma":[0.8999401,0.09286643,0.004402713,0.0009994428,0.001667719,0.0001236036],"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":[0.0006277413,0.0002380396,0.0377106,0.0002992635,0.001219684,0.00005528518,0.07070966,0.000005496409,0.0006528874,0.09216312,0.015846,0.7804722],"study_design_scores_gemma":[0.001097752,0.0005656317,0.1135738,0.00343952,0.0001535922,0.00001673726,0.07350672,0.00002425691,0.0058805,0.7965027,0.004254922,0.0009838946],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.3943254,0.001684918,0.00008710084,0.006226783,0.0009649483,0.003195347,0.0006626923,0.00004820155,0.5928046],"genre_scores_gemma":[0.9936681,0.0001469902,0.0001277085,0.0001815035,0.0003341317,0.00008976295,0.00000658516,0.00007347389,0.005371741],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.7794883,"threshold_uncertainty_score":0.9999576,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.5543906980281975,"score_gpt":0.515399920885707,"score_spread":0.03899077714249055,"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."}}