{"id":"W4327793320","doi":"10.1017/ash.2023.124","title":"Characterizing burnout among healthcare epidemiologists in the early phases of the COVID-19 pandemic: A study of the SHEA Research Network","year":2023,"lang":"en","type":"article","venue":"Antimicrobial Stewardship & Healthcare Epidemiology","topic":"Healthcare professionals’ stress and burnout","field":"Health Professions","cited_by":8,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Burnout; Staffing; Stressor; Health care; Pandemic; Economic shortage; Coronavirus disease 2019 (COVID-19); Nursing; Medicine; 2019-20 coronavirus outbreak; Psychology; Clinical psychology; Political science; Pathology","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":["metaresearch","metaepi_narrow","sts","research_integrity"],"consensus_categories":["metaresearch","research_integrity"],"category_scores_codex":[0.07833703,0.0006586738,0.002710486,0.0004738097,0.004929467,0.00001167165,0.003240421,0.001520013,0.000064332],"category_scores_gemma":[0.03384908,0.0003453672,0.0005614984,0.004389742,0.001773004,0.0001593567,0.002103673,0.007519383,0.00003336973],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008190402,"about_ca_system_score_gemma":0.004134129,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.215163,"about_ca_topic_score_gemma":0.1037052,"domain_scores_codex":[0.882914,0.1047724,0.005565115,0.001432728,0.001067734,0.004248038],"domain_scores_gemma":[0.94444,0.04831858,0.003062271,0.002570797,0.0009995187,0.0006088187],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0004302963,0.0003310775,0.9569649,0.001998844,0.00005694182,0.00001834986,0.02347573,0.0001476647,0.0001326333,0.00180895,0.01318272,0.001451922],"study_design_scores_gemma":[0.00145749,0.0007970638,0.9668717,0.003828146,0.00002992904,0.00001902192,0.01795252,0.00006349498,0.000009116734,0.004232956,0.004440834,0.0002977248],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7971116,0.001841971,0.00001224125,0.1907402,0.002868266,0.006954466,0.0002749535,0.0001254901,0.00007080021],"genre_scores_gemma":[0.9558843,0.002267506,0.00004270824,0.03931298,0.001203425,0.0009477513,0.00006831505,0.00007966126,0.0001933236],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1587727,"threshold_uncertainty_score":0.9998998,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.4027902243281305,"score_gpt":0.5385308355546314,"score_spread":0.1357406112265009,"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."}}