{"id":"W2290337742","doi":"10.29173/alr1313","title":"E-Racing Racial Profiling","year":2004,"lang":"en","type":"article","venue":"Alberta Law Review","topic":"Hate Speech and Cyberbullying Detection","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Windsor","funders":"","keywords":"Racial profiling; Profiling (computer programming); Charter; Reasonable suspicion; Legislation; Political science; Supreme court; Law; Criminology; Sociology; Computer science; Race (biology)","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":true,"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":[0.004983303,0.0002091523,0.0002374133,0.002486359,0.01121992,0.005323811,0.001358804,0.003217775,0.01749919],"category_scores_gemma":[0.01425514,0.0002728041,0.0002536531,0.002323475,0.003606227,0.001963483,0.002330404,0.001803881,0.002148015],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.01299027,"about_ca_system_score_gemma":0.04474742,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.8144239,"about_ca_topic_score_gemma":0.9063671,"domain_scores_codex":[0.9943618,0.0009221938,0.0001820577,0.0003027772,0.0025215,0.001709654],"domain_scores_gemma":[0.9878269,0.002514568,0.0004632786,0.0006472672,0.007116084,0.00143186],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00002919925,0.00007931513,0.01635608,0.0001508711,0.000009496513,0.0005441549,0.005109608,0.0003002903,0.0007002209,0.2036919,0.5638512,0.2091777],"study_design_scores_gemma":[0.000009279167,0.00002173749,0.02153442,0.0001236062,0.00001532464,0.0002032576,0.005492919,0.0003433829,0.0006134343,0.004992303,0.9666166,0.00003381016],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.0286638,0.004322554,0.003007639,0.07209955,0.001159631,0.0002299101,0.0003039346,0.0002302687,0.8899826],"genre_scores_gemma":[0.3189994,0.005712237,0.002915475,0.03904631,0.0004150655,0.00007727793,0.0002955289,0.00007620969,0.6324626],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8144239,"threshold_uncertainty_score":0.3733379,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01166913195435741,"score_gpt":0.2512083401308324,"score_spread":0.239539208176475,"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."}}