{"id":"W3123252993","doi":"","title":"Can Making It Harder to Convict Criminals Ever Reduce Crime","year":2004,"lang":"en","type":"article","venue":"SSRN Electronic Journal","topic":"Law, Economics, and Judicial Systems","field":"Economics, Econometrics and Finance","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"Thompson Rivers University","funders":"","keywords":"Commit; Convict; Burden of proof; Conviction; Incentive; Payment; Deterrence (psychology); Criminal Conviction; Order (exchange); Actuarial science; Criminology; Computer security; Business; Economics; Political science; Law; Psychology; Computer science; Microeconomics; Finance","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":[0.005106369,0.0007835552,0.0009936616,0.001352784,0.001048063,0.002587324,0.001420282,0.005249269,0.01329365],"category_scores_gemma":[0.06056275,0.0004828233,0.0005072216,0.0008323463,0.002849329,0.004654631,0.002643398,0.001532549,0.004094474],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008186697,"about_ca_system_score_gemma":0.00185211,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002194387,"about_ca_topic_score_gemma":0.002668986,"domain_scores_codex":[0.9956278,0.001839319,0.0001841837,0.0005229981,0.0007885934,0.001037092],"domain_scores_gemma":[0.9550744,0.02110396,0.01359127,0.004029961,0.002274293,0.003926108],"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":[0.002223811,0.004741727,0.1102126,0.001823599,0.0009598917,0.001439427,0.003514237,0.04522003,0.01984583,0.2821831,0.07220303,0.4556326],"study_design_scores_gemma":[0.0009510299,0.003658829,0.2884778,0.0007095297,0.0005131987,0.002556629,0.003741265,0.0232499,0.008235271,0.5379783,0.1295649,0.0003633777],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7142779,0.004241904,0.0312191,0.1452034,0.001323801,0.0001729442,0.00053065,0.0005542602,0.1024759],"genre_scores_gemma":[0.9786653,0.001112319,0.006916145,0.006355039,0.0009955432,0.0000836621,0.0001447811,0.00006061078,0.005666562],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01329365,"threshold_uncertainty_score":0.04447168,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03530837218796366,"score_gpt":0.2556065328460529,"score_spread":0.2202981606580893,"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."}}