{"id":"W2945470204","doi":"10.1097/nna.0000000000000760","title":"Informatics Competencies for Nurse Leaders","year":2019,"lang":"en","type":"article","venue":"JONA The Journal of Nursing Administration","topic":"Electronic Health Records Systems","field":"Health Professions","cited_by":56,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Public Health; Multiple Sclerosis Society of Canada; University of Toronto; Centre for Addiction and Mental Health","funders":"","keywords":"Informatics; Health informatics; Suite; Health Administration Informatics; Knowledge management; Core competency; Identification (biology); Engineering informatics; Medical education; Nursing; Medicine; Psychology; Computer science; Political science; Business","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":[0.002763215,0.0001097032,0.0002788487,0.00009492223,0.000444355,0.00001337353,0.0002196679,0.0001387162,0.00004187386],"category_scores_gemma":[0.0002419495,0.00007226617,0.00008829105,0.0001250055,0.00007195327,0.0002850411,0.000003757978,0.0006469414,0.00007202054],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005489031,"about_ca_system_score_gemma":0.001877441,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000006912845,"about_ca_topic_score_gemma":0.00002553321,"domain_scores_codex":[0.9975221,0.0004047311,0.00127235,0.00004837714,0.0003505162,0.0004018918],"domain_scores_gemma":[0.9966385,0.001268325,0.001347505,0.000197535,0.0004454585,0.0001026959],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"qualitative","study_design_gemma":"qualitative","study_design_scores_codex":[0.007452577,0.001180345,0.03103953,0.005763258,0.0004326787,0.000005012911,0.4198678,0.0008786781,0.01319181,0.04554712,0.3779351,0.09670606],"study_design_scores_gemma":[0.007191444,0.01099672,0.01440665,0.00829742,0.0003975938,0.0007358003,0.6599885,0.01506196,0.001197997,0.006673298,0.2744371,0.0006154931],"study_design_candidate":"qualitative","study_design_consensus":"qualitative","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.954275,0.000384909,0.01090703,0.0170764,0.005845732,0.001856136,0.00001053085,0.00003341277,0.009610849],"genre_scores_gemma":[0.9950262,0.00002990104,0.001927313,0.0007073304,0.0007106623,0.00001037587,0.000005751933,0.00001815819,0.001564297],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2401207,"threshold_uncertainty_score":0.3417664,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1248868376645496,"score_gpt":0.4832508434085985,"score_spread":0.3583640057440489,"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."}}