{"id":"W1978435309","doi":"10.1016/j.ijmedinf.2012.12.006","title":"National efforts to improve health information system safety in Canada, the United States of America and England","year":2013,"lang":"en","type":"article","venue":"International Journal of Medical Informatics","topic":"Electronic Health Records Systems","field":"Health Professions","cited_by":77,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Victoria","funders":"Health Canada","keywords":"SAFER; Certification; Health information technology; Procurement; Software deployment; Variety (cybernetics); Patient safety; Information technology; Usability; Medicine; Business; Public relations; Health care; Computer science; Political science; Marketing; Computer security","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":true,"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":[0.007274398,0.0002461798,0.0003775161,0.003328761,0.005222449,0.004492471,0.001818983,0.001831803,0.002851005],"category_scores_gemma":[0.02910095,0.0004070096,0.0007808435,0.003701744,0.002190754,0.001912478,0.003754374,0.003067146,0.0002525058],"about_ca_system_candidate":true,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0825372,"about_ca_system_score_gemma":0.2912174,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9892267,"about_ca_topic_score_gemma":0.9927,"domain_scores_codex":[0.9899114,0.0009698221,0.0005598765,0.0003894954,0.005401694,0.00276782],"domain_scores_gemma":[0.950753,0.005239931,0.004223969,0.0009250312,0.02675665,0.01210133],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0004449713,0.0005231258,0.7307436,0.0007409221,0.0002307036,0.0003392054,0.01757227,0.001728552,0.00125361,0.01407146,0.09315895,0.1391926],"study_design_scores_gemma":[0.00004278459,0.00009278685,0.9415283,0.0004494453,0.00007913822,0.00009410532,0.0127424,0.001280014,0.0005571647,0.0006446855,0.04244818,0.00004095102],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7138821,0.006387984,0.001501772,0.2106985,0.0006536431,0.000365198,0.00493523,0.000316388,0.06125925],"genre_scores_gemma":[0.9665378,0.002563539,0.001914017,0.01640884,0.0001116101,0.00007287194,0.001689437,0.0000336901,0.01066815],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9174628,"threshold_uncertainty_score":0.5988522,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01599561710133241,"score_gpt":0.3599937902233589,"score_spread":0.3439981731220265,"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."}}