{"id":"W2105148141","doi":"10.1177/1094428104263674","title":"Uncovering Faking Samples in Applicant, Incumbent, and Experimental Data Sets: An Application of Mixed-Model Item Response Theory","year":2004,"lang":"en","type":"article","venue":"Organizational Research Methods","topic":"Behavioral and Psychological Studies","field":"Psychology","cited_by":148,"is_retracted":false,"has_abstract":true,"ca_institutions":"Wilfrid Laurier University","funders":"","keywords":"Psychology; Personality; Sample (material); Social psychology; Test (biology); Item response theory; Personality test; Big Five personality traits; Class (philosophy); Response bias; Econometrics; Psychometrics; Test validity; Developmental psychology; Mathematics; Computer science; Artificial intelligence","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":[],"consensus_categories":[],"category_scores_codex":[0.006952399,0.0001283616,0.0002090385,0.0001806849,0.0001790537,0.0000289563,0.0005062221,0.0001215412,0.0002199769],"category_scores_gemma":[0.0009913542,0.0001128897,0.00001431691,0.0008125689,0.00033807,0.0001699368,0.0005813037,0.0002784157,0.00000992995],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001109344,"about_ca_system_score_gemma":0.00006468935,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003067484,"about_ca_topic_score_gemma":0.00004741715,"domain_scores_codex":[0.9965862,0.001819184,0.0003219009,0.0006022536,0.0003642845,0.0003061967],"domain_scores_gemma":[0.9976161,0.001504888,0.00007546476,0.0005553826,0.0001471701,0.00010107],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","study_design_scores_codex":[0.003518355,0.002261618,0.0848323,0.00004345146,0.00008129911,0.00001634528,0.007596717,0.001284181,0.4605525,0.2600552,0.0001700085,0.179588],"study_design_scores_gemma":[0.003057582,0.0007077002,0.7275845,0.00007382068,0.00002389099,0.00003931259,0.009935775,0.001238002,0.03327008,0.2205354,0.002921428,0.0006124371],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8445969,0.0006963741,0.1535026,0.0002073107,0.00004070584,0.0003520732,0.0001105352,0.00002968993,0.0004638411],"genre_scores_gemma":[0.9201664,0.00002817212,0.07947171,0.00005264101,0.00003442424,0.00008037444,0.000102919,0.0000243915,0.00003900049],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6427522,"threshold_uncertainty_score":0.460351,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.5198422274660762,"score_gpt":0.5916335378818836,"score_spread":0.07179131041580733,"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."}}