{"id":"W2794674254","doi":"10.1097/cin.0000000000000434","title":"Factors Associated With Canadian Nurses' Informatics Competency","year":2018,"lang":"en","type":"article","venue":"CIN Computers Informatics Nursing","topic":"Electronic Health Records Systems","field":"Health Professions","cited_by":76,"is_retracted":false,"has_abstract":true,"ca_institutions":"St. Lawrence College; University of Alberta","funders":"","keywords":"Informatics; Health informatics; Medical education; Computer literacy; Preparedness; Descriptive statistics; Health Administration Informatics; Nursing; Public health informatics; Medicine; Psychology; Knowledge management; Computer science; Health education; Engineering; Public health; Political science","routes":{"ca_aff":true,"ca_fund":false,"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":[0.00182107,0.0001590668,0.0001661679,0.001033323,0.001864289,0.001037724,0.0004860635,0.0002519397,0.003013409],"category_scores_gemma":[0.01322236,0.0001514036,0.0002534515,0.001453131,0.0007974751,0.0003111903,0.0008046106,0.0005006164,0.0001524559],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.01267839,"about_ca_system_score_gemma":0.03048779,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9613514,"about_ca_topic_score_gemma":0.9758587,"domain_scores_codex":[0.9983644,0.0001593219,0.0001029358,0.0001057401,0.0008808882,0.0003866924],"domain_scores_gemma":[0.993081,0.001513367,0.001094564,0.0001724377,0.002673756,0.00146488],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00002316606,0.00003537837,0.9802608,0.00003959402,0.000009673995,0.00008133453,0.002686547,0.0001343737,0.000120675,0.0001735968,0.001120116,0.01531479],"study_design_scores_gemma":[0.000001757365,0.00001201753,0.9966105,0.00002584117,0.000003114121,0.00003674595,0.002069134,0.0001473721,0.00003911583,0.00003359762,0.001016015,0.000004829504],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9918235,0.0003371532,0.0001260217,0.0009131765,0.00001186366,0.00003339332,0.000353351,0.000007192195,0.006394429],"genre_scores_gemma":[0.9982029,0.0002999277,0.0002353928,0.00008886577,0.000004429791,0.00001201291,0.0002564683,0.000002008481,0.0008980175],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.03864861,"threshold_uncertainty_score":0.09198856,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06857885462747616,"score_gpt":0.3841958469858419,"score_spread":0.3156169923583657,"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."}}