{"id":"W4415815624","doi":"10.1001/amajethics.2025.815","title":"How Could Legal Standards Promote Equitable Access to EHRs?","year":2025,"lang":"en","type":"article","venue":"The AMA Journal of Ethic","topic":"Electronic Health Records Systems","field":"Health Professions","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Artificial Intelligence in Medicine (Canada)","funders":"","keywords":"Health records; Confidentiality; The Internet; Access to medicines; Legal action; Access to information","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":[0.1272957,0.0009733704,0.001393374,0.003746202,0.008411689,0.02054674,0.00643827,0.02771401,0.01501349],"category_scores_gemma":[0.3197703,0.001046162,0.002032478,0.002643009,0.02610081,0.03535055,0.01177486,0.02262658,0.003157405],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.01810588,"about_ca_system_score_gemma":0.06167075,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.03942398,"about_ca_topic_score_gemma":0.02363821,"domain_scores_codex":[0.9052873,0.04133806,0.005808191,0.007160475,0.03133867,0.009067271],"domain_scores_gemma":[0.7616481,0.1347847,0.01127473,0.01597982,0.0640228,0.01228988],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.00002741188,0.0001242494,0.001658038,0.0001750809,0.00003119864,0.0001691034,0.001920921,0.0007882845,0.0001200884,0.8623627,0.09485139,0.03777148],"study_design_scores_gemma":[0.00008326949,0.00007120128,0.002056707,0.0023486,0.00003809887,0.0001862693,0.003541595,0.001238499,0.0003521583,0.7228594,0.2671299,0.00009421436],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"commentary","genre_gemma":"commentary","genre_scores_codex":[0.003553459,0.004283676,0.01236355,0.9343143,0.002737861,0.0001250119,0.000159255,0.0001284681,0.04233449],"genre_scores_gemma":[0.2563569,0.01110949,0.04468962,0.6558044,0.009603143,0.0008695858,0.0006777192,0.0004997951,0.02038937],"genre_candidate":"commentary","genre_consensus":"commentary","teacher_disagreement_score":0.1272957,"threshold_uncertainty_score":0.6732118,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1050469503819077,"score_gpt":0.5257971092889936,"score_spread":0.4207501589070859,"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."}}