{"id":"W4405930578","doi":"10.1101/2024.12.30.24319785","title":"Advancing Healthcare AI Governance: A Comprehensive Maturity Model Based on Systematic Review","year":2024,"lang":"en","type":"preprint","venue":"medRxiv","topic":"Artificial Intelligence in Healthcare and Education","field":"Medicine","cited_by":8,"is_retracted":false,"has_abstract":true,"ca_institutions":"Artificial Intelligence in Medicine (Canada)","funders":"","keywords":"Maturity (psychological); Corporate governance; Capability Maturity Model; Health care; Systematic review; Political science; Business; Computer science; MEDLINE; Finance","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":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.1811246,0.002364473,0.004944418,0.04104639,0.001544676,0.008423203,0.003819956,0.003812,0.002138158],"category_scores_gemma":[0.3482536,0.001826458,0.0121896,0.02528037,0.002085116,0.01475063,0.007087074,0.0029058,0.0004191422],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.01401242,"about_ca_system_score_gemma":0.05609032,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01081433,"about_ca_topic_score_gemma":0.01789503,"domain_scores_codex":[0.9053889,0.04774272,0.02681906,0.004673774,0.01387583,0.001499769],"domain_scores_gemma":[0.6758821,0.2328969,0.03455549,0.01066158,0.04358067,0.002423222],"domain_codex":null,"domain_gemma":"evaluation","domain_candidate":"evaluation","domain_consensus":null,"study_design_codex":"systematic_review","study_design_gemma":"systematic_review","study_design_scores_codex":[0.0003159243,0.0001453035,0.02186382,0.4759484,0.01760387,0.0003010258,0.004119326,0.01059957,0.0006615067,0.04913133,0.01314953,0.4061604],"study_design_scores_gemma":[0.0003456677,0.0004642562,0.0145222,0.8137511,0.03802698,0.000417284,0.002661486,0.01322776,0.0007416593,0.0608282,0.05474386,0.0002695826],"study_design_candidate":"systematic_review","study_design_consensus":"systematic_review","genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.01945374,0.7779694,0.1215912,0.04493569,0.0006766715,0.01935999,0.007283456,0.0007531238,0.007976679],"genre_scores_gemma":[0.2579822,0.3566078,0.341294,0.007505605,0.0002922656,0.02833992,0.007338895,0.0001200954,0.0005193978],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.8188754,"threshold_uncertainty_score":0.9578898,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.09835010701167649,"score_gpt":0.4292849795365841,"score_spread":0.3309348725249076,"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."}}