{"id":"W2403798605","doi":"10.1177/2153368716646163","title":"The Impact of Police Deployment on Racial Disparities in Discretionary Searches","year":2016,"lang":"en","type":"article","venue":"Race and Justice","topic":"Crime Patterns and Interventions","field":"Social Sciences","cited_by":16,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Software deployment; Police department; Mile; Black spot; Criminology; Race (biology); Quarter (Canadian coin); Demographic economics; Computer security; Political science; Geography; Psychology; Engineering; Computer science; Sociology; Economics","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003123944,0.00003677793,0.0000541885,0.00002575644,0.00023734,0.00002554083,0.00007151524,0.00002052881,0.0001151283],"category_scores_gemma":[0.0001232557,0.00001869937,0.00004590984,0.00005326954,0.0001988388,0.0000897447,0.00002554307,0.00003718156,0.000008130336],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004476559,"about_ca_system_score_gemma":0.00003521882,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02441643,"about_ca_topic_score_gemma":0.01076826,"domain_scores_codex":[0.9994981,0.0001001606,0.00008673031,0.00006468897,0.0001153214,0.0001349891],"domain_scores_gemma":[0.9994205,0.0004316268,0.0000277572,0.00005879208,0.0000240048,0.00003737089],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0007024083,0.0009088989,0.4887892,0.0001369506,0.0001368901,0.000005776494,0.06969174,0.00004393073,0.003195548,0.2769924,0.03192163,0.1274747],"study_design_scores_gemma":[0.0004575561,0.0002945899,0.9703718,0.0002514782,0.00003670224,6.481321e-7,0.01720546,0.00004889733,0.000217511,0.002124643,0.008871939,0.0001187816],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9895794,0.0002105604,0.00006428893,0.004472476,0.00006478261,0.00007346138,0.00002030564,0.000006114713,0.005508607],"genre_scores_gemma":[0.9965554,0.0008526718,0.000004636845,0.00002047065,0.0001091021,0.000006287515,4.633112e-7,0.000002510053,0.002448458],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4815826,"threshold_uncertainty_score":0.98208,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05307353367609439,"score_gpt":0.4118575065002892,"score_spread":0.3587839728241948,"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."}}