{"id":"W2736744013","doi":"10.1177/0093854817719482","title":"Broken Legs, Clinical Overrides, and Recidivism Risk: An Analysis of Decisions to Adjust Risk Levels With the LS/CMI","year":2017,"lang":"en","type":"article","venue":"Criminal Justice and Behavior","topic":"Psychopathy, Forensic Psychiatry, Sexual Offending","field":"Psychology","cited_by":53,"is_retracted":false,"has_abstract":true,"ca_institutions":"Centre Intégré Universitaire de Santé et de Services Sociaux du Centre-Sud-de-l'Île-de-Montréal; Université de Montréal; Institut national de psychiatrie légale Philippe-Pinel","funders":"","keywords":"Recidivism; Risk assessment; Psychological intervention; Psychology; Risk management; Applied psychology; Criminal justice; Actuarial science; Sample (material); Identification (biology); Risk analysis (engineering); Medicine; Psychiatry; Computer science; Business; Criminology; Computer security; Biology","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.01061496,0.0002537305,0.0003605435,0.00204618,0.0006512632,0.001268972,0.0006115384,0.0005249752,0.001821295],"category_scores_gemma":[0.06530206,0.0001795935,0.0007015437,0.001044177,0.001211128,0.0009361445,0.001320783,0.001445016,0.0001796842],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001058891,"about_ca_system_score_gemma":0.0007887254,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002191535,"about_ca_topic_score_gemma":0.002806482,"domain_scores_codex":[0.9942275,0.003466528,0.0003959773,0.0002551935,0.001249087,0.0004056848],"domain_scores_gemma":[0.9470125,0.0334561,0.01376689,0.001355449,0.001971139,0.002437978],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0004190777,0.0001253906,0.9856301,0.00001029399,0.00006402848,0.0000760238,0.000652303,0.0002139581,0.0000546962,0.000186305,0.0001244764,0.0124434],"study_design_scores_gemma":[0.00001281171,0.0004420853,0.9946443,0.0000250988,0.00003242802,0.0001916479,0.00161877,0.002361522,0.00008423228,0.0003844455,0.0001917016,0.00001098277],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9986045,0.00007997456,0.0002426772,0.0001867205,0.000003557997,0.00002593642,0.00003055264,0.000003793346,0.0008223779],"genre_scores_gemma":[0.9993495,0.00003176293,0.0003930191,0.00002489447,0.000005606165,0.00001941283,0.00004086486,0.000001951944,0.0001329303],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01061496,"threshold_uncertainty_score":0.05613798,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1501232691040095,"score_gpt":0.4413688501576742,"score_spread":0.2912455810536647,"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."}}