{"id":"W4304845711","doi":"10.1177/08404704221125368","title":"Equity within AI systems: What can health leaders expect?","year":2022,"lang":"en","type":"article","venue":"Healthcare Management Forum","topic":"Artificial Intelligence in Healthcare and Education","field":"Medicine","cited_by":89,"is_retracted":false,"has_abstract":true,"ca_institutions":"York University","funders":"","keywords":"Equity (law); Health equity; Public relations; Work (physics); Business; Political science; Health care; Psychology; Medicine; Engineering; Law","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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","sts"],"consensus_categories":[],"category_scores_codex":[0.001401069,0.0002523268,0.0004651896,0.0003973031,0.001305693,0.0001280289,0.0002600649,0.00007251397,0.0002101481],"category_scores_gemma":[0.00002701829,0.0002668847,0.0001182019,0.0006892861,0.00008626233,0.0002458578,0.0003814049,0.0006755316,0.0000671061],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002296105,"about_ca_system_score_gemma":0.0008086697,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01253377,"about_ca_topic_score_gemma":0.001987515,"domain_scores_codex":[0.9959231,0.0003554343,0.00099307,0.0006370497,0.000963554,0.001127778],"domain_scores_gemma":[0.9981987,0.00004692874,0.0003155734,0.0007321208,0.0001464107,0.0005602501],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"qualitative","study_design_scores_codex":[0.0006345019,0.000915723,0.03495182,0.009894996,0.0002711,0.0002442025,0.04845983,0.001851519,0.000008772788,0.1088199,0.2216699,0.5722778],"study_design_scores_gemma":[0.0002299066,0.001872162,0.0009445379,0.0006676553,0.0000462882,0.0001159102,0.8530638,0.00173445,0.00007216119,0.002224676,0.1386493,0.0003791483],"study_design_candidate":"qualitative","study_design_consensus":null,"genre_codex":"commentary","genre_gemma":"empirical","genre_scores_codex":[0.04967835,0.01450393,0.0009712819,0.9146571,0.0116256,0.005788169,0.00004366,0.000537387,0.002194561],"genre_scores_gemma":[0.9262009,0.001246114,0.0001762965,0.06809388,0.0002852396,0.0008738743,0.0002283339,0.00005334478,0.002841964],"genre_candidate":"commentary","genre_consensus":null,"teacher_disagreement_score":0.8765226,"threshold_uncertainty_score":0.9999945,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2154729147325315,"score_gpt":0.4572062369215564,"score_spread":0.2417333221890249,"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."}}