{"id":"W3202375715","doi":"10.1097/ncq.0000000000000600","title":"Workplace Predictors of Quality and Safe Patient Care Delivery Among Nurses Using Machine Learning Techniques","year":2021,"lang":"en","type":"article","venue":"Journal of Nursing Care Quality","topic":"Nursing education and management","field":"Nursing","cited_by":12,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"","keywords":"Quality (philosophy); Quality management; MEDLINE; Nursing; Patient safety; Patient care; Medical emergency; Medicine; Computer science; Psychology; Health care; Operations management; Engineering","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002535561,0.0003283616,0.0004019676,0.001468552,0.00037729,0.001023342,0.0003503531,0.0003702302,0.001190159],"category_scores_gemma":[0.01134153,0.0001578328,0.0007229938,0.001145824,0.0001772148,0.000392834,0.0005009631,0.0007180513,0.0001816502],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005697605,"about_ca_system_score_gemma":0.001242808,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0139877,"about_ca_topic_score_gemma":0.01308555,"domain_scores_codex":[0.9990951,0.0004354368,0.00008531086,0.0001255917,0.0001527416,0.0001059519],"domain_scores_gemma":[0.9915296,0.006197899,0.001003308,0.0002428123,0.0006556506,0.0003707211],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001340692,0.0003689682,0.9614915,0.00003708665,0.0001617067,0.00002861926,0.0002039698,0.00476108,0.0001633927,0.00005587892,0.0003492043,0.03224448],"study_design_scores_gemma":[0.00002567127,0.0003479676,0.8279055,0.0001069522,0.0001241472,0.00006467046,0.0007495043,0.1692904,0.0003762551,0.0006270339,0.0003570909,0.00002480265],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9953933,0.0001740947,0.003545055,0.0001676659,0.00001114369,0.00002806805,0.0002318144,0.00003017581,0.0004187673],"genre_scores_gemma":[0.9973106,0.00006296272,0.002235616,0.00001072927,0.000007186327,0.00002615232,0.0002312862,0.000002943188,0.0001125136],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0139877,"threshold_uncertainty_score":0.02781254,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03698035093871915,"score_gpt":0.3785958245427114,"score_spread":0.3416154736039922,"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."}}