{"id":"W2035961277","doi":"10.1007/s10979-008-9137-9","title":"The reliability of lie detection performance.","year":2008,"lang":"en","type":"article","venue":"Law and Human Behavior","topic":"Deception detection and forensic psychology","field":"Psychology","cited_by":30,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto; McGill University; Queen's University; Ontario Tech University","funders":"Social Sciences and Humanities Research Council of Canada","keywords":"Deception; Psychology; Lie detection; Reliability (semiconductor); Legal psychology; Social psychology; CLIPS; Lying; Cognitive psychology; Developmental psychology; Artificial intelligence; Computer science","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0001471582,0.00007117259,0.0001001153,0.00002681776,0.0005316605,0.000006579738,0.00006949201,0.00008667693,0.0006754037],"category_scores_gemma":[0.000002912028,0.00005186073,0.0000461108,0.0000533272,0.0006771052,0.00004123506,0.00001559282,0.0001360219,0.00007546111],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000009513759,"about_ca_system_score_gemma":0.000002963401,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001165538,"about_ca_topic_score_gemma":0.000167626,"domain_scores_codex":[0.999368,0.00004781903,0.0002052724,0.0001678936,0.00007591979,0.0001350621],"domain_scores_gemma":[0.9995142,0.00002426307,0.0000699393,0.0003045456,0.00004646463,0.0000405856],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0009697736,0.001965886,0.3786612,0.00004335944,0.00008896233,0.00004216939,0.007106917,0.000001474832,0.0312124,0.2827422,0.008196533,0.2889691],"study_design_scores_gemma":[0.0005377998,0.0003944232,0.9321911,0.000002055889,0.00002109249,0.000143524,0.0001187779,9.273782e-7,0.001446331,0.0003104933,0.06475269,0.00008077284],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9497398,0.00003352372,0.00001304089,0.00002514935,0.0008370353,0.0001232968,0.000001991484,0.00004365463,0.04918257],"genre_scores_gemma":[0.9944221,0.0000222071,0.000009774577,0.0001026531,0.00006949586,0.00005594859,0.000001328546,0.000007620064,0.005308914],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5535299,"threshold_uncertainty_score":0.7395197,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03253387570398304,"score_gpt":0.3096017257690107,"score_spread":0.2770678500650277,"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."}}