{"id":"W4388494039","doi":"10.1016/j.healthpol.2023.104938","title":"AI maturity in health care: An overview of 10 OECD countries","year":2023,"lang":"en","type":"article","venue":"Health Policy","topic":"Artificial Intelligence in Healthcare and Education","field":"Medicine","cited_by":28,"is_retracted":false,"has_abstract":false,"ca_institutions":"HEC Montréal; Université de Montréal; Université du Québec","funders":"","keywords":"Maturity (psychological); Health care; Government (linguistics); Capability Maturity Model; Business; Political science; Economic growth; Computer science; Economics","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":[],"consensus_categories":[],"category_scores_codex":[0.0009803141,0.0001164565,0.0004424577,0.0004697189,0.0001367599,0.000008957053,0.00008126965,0.0001038196,0.000192992],"category_scores_gemma":[0.000180794,0.0001137836,0.00004587338,0.0007627633,0.00007190038,0.00009887532,0.00002270739,0.0002482659,0.0003688922],"about_ca_system_candidate":true,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006923866,"about_ca_system_score_gemma":0.006291622,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.1209978,"about_ca_topic_score_gemma":0.008157912,"domain_scores_codex":[0.9978314,0.0002106973,0.000855034,0.0002334004,0.0002678744,0.0006015887],"domain_scores_gemma":[0.9987471,0.0001030465,0.0002114258,0.0003747562,0.0001626793,0.0004009682],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0005835432,0.0006606063,0.06493155,0.04078794,0.00002432695,0.00001753957,0.169894,0.0000665536,0.00002895446,0.07935102,0.1731501,0.4705038],"study_design_scores_gemma":[0.0003438342,0.002973766,0.175418,0.001780432,0.000008894806,0.00003006125,0.01463383,0.0004598514,0.0009630569,0.007937724,0.795137,0.0003135],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"commentary","genre_gemma":"empirical","genre_scores_codex":[0.4069444,0.01451608,0.000008598344,0.5758017,0.0005695054,0.001342292,0.00008042675,0.000203012,0.0005339806],"genre_scores_gemma":[0.9060977,0.01662232,0.0001573382,0.0754236,0.0009194381,0.00005312218,0.000206849,0.00003135683,0.0004882667],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.6219869,"threshold_uncertainty_score":0.9993418,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.3543788466737132,"score_gpt":0.5956670926013276,"score_spread":0.2412882459276144,"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."}}