{"id":"W2809981794","doi":"10.1016/j.apnr.2018.06.014","title":"Estimating the association between burnout and electronic health record-related stress among advanced practice registered nurses","year":2018,"lang":"en","type":"article","venue":"Applied Nursing Research","topic":"Electronic Health Records Systems","field":"Health Professions","cited_by":106,"is_retracted":false,"has_abstract":false,"ca_institutions":"Public Health Ontario; University of Toronto","funders":"American Association of Nurse Practitioners","keywords":"Burnout; Medicine; Documentation; Logistic regression; Electronic health record; Family medicine; Demographics; Clinical psychology; Demography; Health care; Internal medicine","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":["sts","research_integrity"],"consensus_categories":[],"category_scores_codex":[0.01944202,0.0002780274,0.0006007383,0.0002854413,0.005468755,0.0001121736,0.0005007178,0.0004763744,0.00004543956],"category_scores_gemma":[0.004156155,0.0002286415,0.00004390497,0.001257589,0.0005250566,0.0003015401,0.0001208416,0.004543372,0.0002296186],"about_ca_system_candidate":true,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.005792314,"about_ca_system_score_gemma":0.002604107,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002933437,"about_ca_topic_score_gemma":0.001112538,"domain_scores_codex":[0.9881692,0.005063014,0.001316789,0.0008182282,0.001340258,0.003292544],"domain_scores_gemma":[0.9866415,0.009795048,0.001370713,0.0008471356,0.0009475056,0.0003980889],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.0006768187,0.0002632938,0.1071581,0.001125311,0.0003090228,0.000002804099,0.0701494,0.00001709857,0.00049656,0.01893934,0.03762393,0.7632383],"study_design_scores_gemma":[0.01916576,0.01100582,0.3002364,0.03380677,0.0005238748,0.00005224552,0.2284209,0.01144063,0.0006813135,0.1244174,0.2668919,0.003356948],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8597345,0.00167695,0.0007617939,0.03962124,0.001988457,0.007761257,0.00001970439,0.0004274544,0.08800862],"genre_scores_gemma":[0.9926355,0.0001810658,0.001175771,0.0003748674,0.001592946,0.0005449948,0.00003811875,0.0001014613,0.003355224],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.7598813,"threshold_uncertainty_score":0.9980243,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08721664174324041,"score_gpt":0.5197280184670339,"score_spread":0.4325113767237935,"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."}}