{"id":"W4210644018","doi":"10.3899/jrheum.210990","title":"Results From the 2020 Canadian Rheumatology Association’s Workforce and Wellness Survey","year":2022,"lang":"en","type":"article","venue":"The Journal of Rheumatology","topic":"Diversity and Career in Medicine","field":"Social Sciences","cited_by":39,"is_retracted":false,"has_abstract":true,"ca_institutions":"Alberta Bone and Joint Health Institute; Western University; Centre for Advancing Health Outcomes; University of British Columbia; Research Canada; University of Calgary; University of Toronto; Sunnybrook Health Science Centre","funders":"Institute of Musculoskeletal Health and Arthritis; Canadian Institutes of Health Research; Michael Smith Health Research BC; Arthritis Society","keywords":"Medicine; Workforce; Rheumatology; Burnout; Family medicine; Population; Economic shortage; Pandemic; Demography; Internal medicine; Physical therapy; Gerontology; Coronavirus disease 2019 (COVID-19); Environmental health","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":true,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.002169515,0.0004924144,0.0004964621,0.003194321,0.001273633,0.0008913637,0.0008837209,0.0005289292,0.005371498],"category_scores_gemma":[0.006038274,0.0002447172,0.0008220918,0.005781921,0.0001861288,0.0003863701,0.0008672564,0.0006720018,0.001454443],"about_ca_system_candidate":true,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.01154906,"about_ca_system_score_gemma":0.0264245,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9616881,"about_ca_topic_score_gemma":0.9741066,"domain_scores_codex":[0.9959591,0.0002663152,0.0002160519,0.0002358016,0.002585336,0.0007374213],"domain_scores_gemma":[0.9936746,0.0002327985,0.0005868953,0.00007486955,0.004398402,0.001032394],"domain_codex":null,"domain_gemma":"incentives","domain_candidate":"incentives","domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001531579,0.00009847539,0.6899822,0.0006180716,0.0001707307,0.00007015873,0.0004355955,0.0003287866,0.0001638796,0.0002833531,0.2859262,0.02176936],"study_design_scores_gemma":[0.00001421712,0.0000163799,0.9857447,0.00007395555,0.00002182757,0.00001794284,0.0002522026,0.000105616,0.00002639877,0.00002069108,0.01369404,0.00001224356],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"dataset","genre_gemma":"empirical","genre_scores_codex":[0.1560017,0.002389976,0.0005008755,0.004043964,0.0002094735,0.0005958474,0.8003523,0.0001525499,0.03575325],"genre_scores_gemma":[0.5082515,0.003147749,0.002370433,0.003051076,0.0001759634,0.001349054,0.4686055,0.00004624466,0.0130026],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9978305,"threshold_uncertainty_score":0.08379465,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02241723555064169,"score_gpt":0.2546575585635155,"score_spread":0.2322403230128738,"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."}}