{"id":"W2073774823","doi":"10.1097/cin.0000000000000114","title":"Measuring Nursing Informatics Competencies of Practicing Nurses in Korea","year":2014,"lang":"en","type":"article","venue":"CIN Computers Informatics Nursing","topic":"Nursing Diagnosis and Documentation","field":"Nursing","cited_by":33,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Catholic University of Korea; Korea University; Ewha Womans University; University of Victoria","keywords":"Informatics; Health informatics; Construct (python library); Medical education; Construct validity; Descriptive statistics; Nursing; CLARITY; Medicine; Psychology; Knowledge management; Computer science; Patient satisfaction; Engineering","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001784927,0.0002482204,0.0001508902,0.0009174311,0.0003173363,0.000430057,0.000250774,0.0002333551,0.0009370878],"category_scores_gemma":[0.004115017,0.0001819638,0.0001794539,0.0004641283,0.000269351,0.0007110531,0.0009645876,0.0002867297,0.0001987106],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000649014,"about_ca_system_score_gemma":0.001760884,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002561264,"about_ca_topic_score_gemma":0.00781678,"domain_scores_codex":[0.9993821,0.0001647039,0.0001456013,0.0000743243,0.0001327427,0.0001005655],"domain_scores_gemma":[0.9981179,0.0003774878,0.0005010565,0.0001000369,0.0005756677,0.0003279304],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00009137139,0.0004448754,0.9106059,0.0002317154,0.00002664311,0.0001724524,0.005030327,0.0003696656,0.002974287,0.0001915869,0.0007064132,0.07915467],"study_design_scores_gemma":[0.0000133456,0.0003511586,0.9844999,0.0001115078,0.00001709982,0.0003162096,0.01005648,0.0007758426,0.001313755,0.0001254418,0.002401054,0.00001818999],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9980854,0.00006566504,0.0003907288,0.00005307113,0.000003570025,0.00008141513,0.0000833665,0.000003759732,0.001233024],"genre_scores_gemma":[0.9955484,0.0001993227,0.003057646,0.00008483794,0.000001911428,0.000183269,0.0002247942,0.000002697739,0.0006972495],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.002561264,"threshold_uncertainty_score":0.009439647,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02386082772622404,"score_gpt":0.289104059924283,"score_spread":0.2652432321980589,"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."}}