{"id":"W3198677971","doi":"","title":"RACIAL PROFILING AND THE PERILS OF ANCILLARY POLICE POWERS","year":2021,"lang":"en","type":"article","venue":"The Canadian Bar Review","topic":"Criminal Law and Evidence","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Ottawa","funders":"","keywords":"Racial profiling; Harm; Distrust; Supreme court; Proportionality (law); Political science; Law; Accountability; Profiling (computer programming); Criminology; Sociology; Computer science; Race (biology)","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"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":[0.03535822,0.0003945222,0.0008298118,0.005537199,0.01526279,0.01228172,0.002524526,0.003840617,0.003014714],"category_scores_gemma":[0.07858597,0.0006523519,0.0005263566,0.004033736,0.02191214,0.007208621,0.005566429,0.007176631,0.0002199234],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0321506,"about_ca_system_score_gemma":0.09823519,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.6902494,"about_ca_topic_score_gemma":0.8560188,"domain_scores_codex":[0.9508241,0.01408032,0.001501907,0.002880576,0.02432293,0.006390084],"domain_scores_gemma":[0.9472557,0.02502887,0.006202545,0.002486086,0.01623097,0.002795658],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00002707374,0.00001405615,0.005121956,0.0002323696,0.00002883915,0.0001445733,0.003878915,0.0001663542,0.0001900988,0.9401002,0.01077279,0.03932275],"study_design_scores_gemma":[0.00009930416,0.00009582072,0.06076219,0.005172725,0.0003564799,0.0004817459,0.01295006,0.001074616,0.00166146,0.392612,0.5245354,0.0001982216],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"other","genre_gemma":"commentary","genre_scores_codex":[0.08226578,0.05695605,0.009178721,0.3332683,0.002542709,0.0001857115,0.0003012714,0.0000681214,0.5152333],"genre_scores_gemma":[0.9301,0.01476013,0.003203414,0.03768114,0.0008411214,0.0000680728,0.00006686504,0.00003147356,0.01324779],"genre_candidate":"commentary","genre_consensus":null,"teacher_disagreement_score":0.3097506,"threshold_uncertainty_score":0.6231495,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0399597694476228,"score_gpt":0.3306205285925329,"score_spread":0.2906607591449101,"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."}}