{"id":"W3193772858","doi":"","title":"IMPACT OF COVID-19 PANDEMIC ON WELLBEING OF DOCTORS IN KASHMIR","year":2021,"lang":"en","type":"article","venue":"Annals of Medical and Health Sciences Research","topic":"COVID-19 Pandemic Impacts","field":"Economics, Econometrics and Finance","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Pandemic; Medicine; Livelihood; Globe; Coronavirus disease 2019 (COVID-19); Quarter (Canadian coin); China; Workload; 2019-20 coronavirus outbreak; Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2); Socioeconomics; Agriculture; Outbreak; Virology; Disease; Management; Geography","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"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":[0.001093039,0.0001710622,0.0002403565,0.0008004592,0.0008653871,0.001233685,0.0002383771,0.0005345886,0.004205983],"category_scores_gemma":[0.004309983,0.000117707,0.0002391267,0.001256792,0.0006876542,0.0008490296,0.001159849,0.001295299,0.0002307024],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003722918,"about_ca_system_score_gemma":0.002344164,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.04863853,"about_ca_topic_score_gemma":0.04637875,"domain_scores_codex":[0.9992166,0.0002960261,0.00003553331,0.00004007447,0.0001049717,0.0003069353],"domain_scores_gemma":[0.9974389,0.001081331,0.0007031226,0.00003317895,0.0002849596,0.0004584399],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0003159879,0.0002544823,0.9422089,0.000300329,0.0001351305,0.002128983,0.005006338,0.005143746,0.0004288759,0.01627508,0.008081581,0.01972055],"study_design_scores_gemma":[0.00002037665,0.0001941668,0.9589466,0.0002195781,0.00005019575,0.0003881587,0.02443521,0.005242497,0.0002545909,0.004450699,0.005748011,0.00004995444],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9796942,0.001876707,0.0001374529,0.01176156,0.00005093513,0.00001563718,0.000757485,0.000002553196,0.005703542],"genre_scores_gemma":[0.9980116,0.0009238622,0.00004394331,0.0003119757,0.00003039499,0.000004478654,0.0001033267,6.552388e-7,0.0005697264],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.04863853,"threshold_uncertainty_score":0.0967108,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.6025187546433,"score_gpt":0.5790430260151217,"score_spread":0.02347572862817826,"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."}}