{"id":"W3132448575","doi":"10.1111/tri.13853","title":"The higher impact of the COVID‐19 pandemic on resident/fellow training in low‐ and middle‐income countries","year":2021,"lang":"en","type":"letter","venue":"Transplant International","topic":"COVID-19 and healthcare impacts","field":"Medicine","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University Health Centre","funders":"","keywords":"Medicine; Coronavirus disease 2019 (COVID-19); Pandemic; 2019-20 coronavirus outbreak; Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2); Low and middle income countries; Middle income country; Coronavirus Infections; Middle income; Virology; Internal medicine; Developing country; Demographic economics; Economic growth; Outbreak; Infectious disease (medical specialty)","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"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":[0.003051494,0.0001776448,0.0001851553,0.000934325,0.0007846787,0.001186189,0.0004640336,0.0009495495,0.009984989],"category_scores_gemma":[0.01025754,0.0001396997,0.0002708828,0.001122044,0.0008464169,0.001184499,0.001120745,0.001282798,0.0005430236],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005121046,"about_ca_system_score_gemma":0.0008325169,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004857574,"about_ca_topic_score_gemma":0.007594242,"domain_scores_codex":[0.9976397,0.00114584,0.000176455,0.0001903866,0.0003587803,0.0004888448],"domain_scores_gemma":[0.9868355,0.003249583,0.006225178,0.0002912456,0.0008299829,0.002568559],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00007054422,0.00008913757,0.9659548,0.0002697588,0.0000505076,0.0004884743,0.002389532,0.00009220931,0.0002429109,0.0002535162,0.008548532,0.02155009],"study_design_scores_gemma":[0.000004695286,0.00008203869,0.9901761,0.0001864088,0.00001093193,0.000574666,0.004919893,0.0001033665,0.00006859298,0.0001012225,0.003758752,0.00001327353],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"commentary","genre_scores_codex":[0.968954,0.004228116,0.0002658158,0.01911121,0.0007025786,0.00002163608,0.0006836319,0.00001400649,0.006019052],"genre_scores_gemma":[0.9924152,0.002721674,0.0002904296,0.002918768,0.0009950254,0.00001326256,0.000182366,0.000009816003,0.0004534895],"genre_candidate":"commentary","genre_consensus":null,"teacher_disagreement_score":0.009984989,"threshold_uncertainty_score":0.03340316,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1138956782577956,"score_gpt":0.3809162317778672,"score_spread":0.2670205535200715,"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."}}