{"id":"W4414552918","doi":"10.1093/jamia/ocaf133","title":"Towards responsible artificial intelligence in healthcare—getting real about real-world data and evidence","year":2025,"lang":"en","type":"article","venue":"Journal of the American Medical Informatics Association","topic":"Artificial Intelligence in Healthcare and Education","field":"Medicine","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"Artificial Intelligence in Medicine (Canada); Homewood Research Institute; University of Victoria","funders":"","keywords":"Trustworthiness; Foundation (evidence); Health care; Healthcare industry; Health professionals; Meaningful use","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":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.008255123,0.0001163405,0.0004951425,0.0004184913,0.0001436638,0.00006688724,0.0004852684,0.00008992158,0.000008559879],"category_scores_gemma":[0.01823241,0.0000844684,0.00006919311,0.001558823,0.0002209984,0.0004012879,0.0002113821,0.000938385,0.000004595756],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00102559,"about_ca_system_score_gemma":0.003289157,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007675243,"about_ca_topic_score_gemma":0.004040367,"domain_scores_codex":[0.9961371,0.00034282,0.001975671,0.0001142454,0.001119487,0.0003106367],"domain_scores_gemma":[0.9947094,0.001820223,0.002262818,0.0004223901,0.0005590086,0.0002261246],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.0003634675,0.00008543034,0.2838898,0.0002109564,0.00005048521,0.000005528855,0.002716829,0.00002315649,0.0000372613,0.002047793,0.002010464,0.7085589],"study_design_scores_gemma":[0.0001758029,0.001020617,0.8135761,0.009207506,0.0003002685,0.00007849195,0.02222927,0.1231661,0.002547693,0.02546905,0.001861267,0.000367825],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8589785,0.0002362482,0.002302656,0.1369589,0.0007636247,0.0002580255,0.00000387495,0.00001320298,0.0004849412],"genre_scores_gemma":[0.983157,0.006570609,0.004235807,0.005546803,0.0003644814,0.000003653798,0.000004247931,0.000007383866,0.0001100528],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.708191,"threshold_uncertainty_score":0.9989327,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.14646092572584,"score_gpt":0.4826266545243045,"score_spread":0.3361657287984645,"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."}}