{"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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.002148991,0.0002311822,0.0006143835,0.0003199299,0.0003444393,0.0002205582,0.0004986558,0.0001476145,0.0002984926],"category_scores_gemma":[0.0001324402,0.0003124563,0.0002486001,0.0001934592,0.00006787917,0.0002989665,0.00006233911,0.0009448431,0.001389195],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00295906,"about_ca_system_score_gemma":0.0009047575,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001674726,"about_ca_topic_score_gemma":0.002368593,"domain_scores_codex":[0.9959185,0.00002673228,0.001045465,0.0004981607,0.00007027562,0.002440852],"domain_scores_gemma":[0.9988213,0.00002463178,0.0005364047,0.0003366173,0.00006849019,0.0002125547],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.00004312958,0.00006364726,0.002383123,0.00001076071,0.0002137107,0.000007965636,0.001224471,0.0003919909,0.00005408176,0.9934317,0.001247423,0.0009279815],"study_design_scores_gemma":[0.001235672,0.0003132913,0.00222105,0.00006691523,0.00002412966,0.0003657448,0.001652069,0.00002220005,0.0001484165,0.9474172,0.04596038,0.0005729322],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7478812,0.01307546,0.02424055,0.03516462,0.005238172,0.001052371,0.0001292596,0.0001450827,0.1730733],"genre_scores_gemma":[0.9923667,0.00117093,0.0001559146,0.002495598,0.001239312,0.00001491517,0.000003711486,0.00006387667,0.002489099],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2444855,"threshold_uncertainty_score":0.9999328,"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."}}