{"id":"W4414199779","doi":"10.7759/cureus.92382","title":"Artificial Intelligence in Action: Racial and Gender Disparities in Academic Radiology","year":2025,"lang":"en","type":"article","venue":"Cureus","topic":"Artificial Intelligence in Healthcare and Education","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Vancouver General Hospital; Canadian Association of Nurses in Oncology; University of British Columbia","funders":"","keywords":"Workforce; Diversity (politics); Generative grammar; Race (biology); Benchmark (surveying); Ranking (information retrieval); Rank (graph theory); Health equity","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.02423449,0.000664209,0.000493339,0.003704119,0.001765499,0.005929529,0.001557051,0.001091462,0.003996651],"category_scores_gemma":[0.1019846,0.0003128209,0.001208999,0.004164268,0.002860779,0.004996502,0.004142751,0.001579939,0.0005593448],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.004050133,"about_ca_system_score_gemma":0.005386312,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01844639,"about_ca_topic_score_gemma":0.02305262,"domain_scores_codex":[0.9864346,0.009595383,0.000449364,0.001394137,0.001708741,0.0004179131],"domain_scores_gemma":[0.9294475,0.05721676,0.004841446,0.004796812,0.003031891,0.0006656564],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0004273815,0.0002324874,0.5165277,0.001134164,0.0003711806,0.0002443118,0.02313708,0.02198737,0.001098774,0.07841273,0.01278499,0.3436419],"study_design_scores_gemma":[0.0001018481,0.0003875766,0.2706071,0.002531469,0.000612474,0.0005475541,0.02964015,0.2200564,0.005502524,0.388624,0.08106523,0.0003237565],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7534748,0.004658376,0.1360592,0.03905855,0.0005369203,0.0006574666,0.005370199,0.001497278,0.05868718],"genre_scores_gemma":[0.9606342,0.0006988698,0.0340059,0.002211891,0.0000982217,0.00021864,0.001026496,0.00009621045,0.001009588],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02423449,"threshold_uncertainty_score":0.1281658,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.3421793449092771,"score_gpt":0.5088711613022929,"score_spread":0.1666918163930158,"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."}}