{"id":"W2991584397","doi":"10.1016/j.learninstruc.2019.101295","title":"People who cheat on tests accurately predict their performance on future tests","year":2020,"lang":"en","type":"article","venue":"Learning and Instruction","topic":"Memory Processes and Influences","field":"Neuroscience","cited_by":8,"is_retracted":false,"has_abstract":false,"ca_institutions":"Kwantlen Polytechnic University; University of Victoria","funders":"Social Sciences and Humanities Research Council of Canada; Canada Research Chairs","keywords":"Cheating; Overconfidence effect; Harm; Psychology; Test (biology); Affect (linguistics); Social psychology; Incentive; Cognition; Econometrics; Cognitive psychology; Economics; Microeconomics","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":["research_integrity"],"consensus_categories":[],"category_scores_codex":[0.001476829,0.0006719743,0.0006266847,0.00112999,0.0004820095,0.002036776,0.0004409162,0.001745852,0.003727321],"category_scores_gemma":[0.0163087,0.0003121357,0.000527004,0.0006091366,0.0007271394,0.001361749,0.0005981683,0.001378418,0.001983452],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004093924,"about_ca_system_score_gemma":0.0002471596,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003888782,"about_ca_topic_score_gemma":0.006588876,"domain_scores_codex":[0.9991007,0.0002022973,0.00006963042,0.0001354052,0.0003241315,0.0001679335],"domain_scores_gemma":[0.9835329,0.006073468,0.005601508,0.001711592,0.001728297,0.001352211],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0002287494,0.0004971356,0.9817604,0.00002617372,0.0001423106,0.00009394916,0.0003163225,0.0003373149,0.001532764,0.0001666039,0.0006869847,0.01421125],"study_design_scores_gemma":[0.00002167233,0.000292634,0.995007,0.00001645603,0.00008600824,0.0002060002,0.0002802947,0.001621953,0.0009639785,0.0008986459,0.000587569,0.00001761659],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9918011,0.0001695438,0.0004809486,0.0002451173,0.00004592638,0.00001917427,0.0001184488,0.00003374297,0.007085952],"genre_scores_gemma":[0.9968941,0.0001819293,0.0005219688,0.0002498883,0.00003211426,0.00001278738,0.0002406485,0.00001613466,0.001850421],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9982541,"threshold_uncertainty_score":0.01246911,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03495604285124995,"score_gpt":0.2658245615512934,"score_spread":0.2308685187000435,"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."}}