{"id":"W4411778952","doi":"10.1177/00938548251350105","title":"The Impact of Racial Profiling on Consumers in Canadian Retail Settings: A Mixed-Method Study Exploring Negative Emotions","year":2025,"lang":"en","type":"article","venue":"Criminal Justice and Behavior","topic":"Names, Identity, and Discrimination Research","field":"Social Sciences","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Profiling (computer programming); Racial profiling; Psychology; Occupational safety and health; Poison control; Human factors and ergonomics; Advertising; Environmental health; Applied psychology; Business; Medicine; Computer science; Sociology; Race (biology)","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0026353,0.0004996479,0.0006566628,0.001425401,0.01032731,0.002372546,0.0009398342,0.0006743849,0.00177997],"category_scores_gemma":[0.004598735,0.0004732573,0.0005108239,0.001585032,0.001970522,0.0006616016,0.001465517,0.001127291,0.0001634887],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.01141235,"about_ca_system_score_gemma":0.01335795,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.862958,"about_ca_topic_score_gemma":0.948745,"domain_scores_codex":[0.9981275,0.0004190523,0.00006198341,0.0001917222,0.0006289017,0.0005708151],"domain_scores_gemma":[0.9977047,0.0003276174,0.0004890767,0.0001068137,0.000983146,0.0003887715],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0005927644,0.001133193,0.6828825,0.0001849212,0.00008552401,0.0005726477,0.283841,0.00006025146,0.002560006,0.0004251155,0.00132985,0.02633209],"study_design_scores_gemma":[0.00001794806,0.0003955856,0.701173,0.00008704121,0.00005131994,0.000215373,0.2947415,0.0001676858,0.0003930359,0.0000825548,0.002602082,0.00007290982],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9989008,0.00007496776,0.00005911053,0.00007114645,0.00000746612,0.00008154452,0.00006715934,0.000001035411,0.0007367619],"genre_scores_gemma":[0.9979786,0.0002280118,0.0003428391,0.0002166937,0.00001066099,0.00009048234,0.00009225964,0.00000345009,0.00103689],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.137042,"threshold_uncertainty_score":0.2756981,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1107959811168321,"score_gpt":0.4567615945314563,"score_spread":0.3459656134146242,"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."}}