{"id":"W2321311939","doi":"10.1177/1090198115606918","title":"The Global Epidemiologic Transition","year":2016,"lang":"en","type":"article","venue":"Health Education & Behavior","topic":"COVID-19 epidemiological studies","field":"Mathematics","cited_by":38,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"Epidemiological transition; Context (archaeology); Relevance (law); Global health; Public health; Nutrition transition; Environmental health; Construct (python library); Paradigm shift; Medicine; Disease; Burden of disease; Transition (genetics); Gerontology; Economic growth; Political science; Geography; Population; Computer science; Obesity; 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0043041,0.0003470089,0.0004228729,0.00264436,0.001914103,0.004320503,0.0006099929,0.001859535,0.006895337],"category_scores_gemma":[0.00947209,0.0002127342,0.0005077527,0.003643214,0.007521212,0.007197105,0.006578205,0.003053681,0.000616901],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003014343,"about_ca_system_score_gemma":0.003071225,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005192737,"about_ca_topic_score_gemma":0.003892299,"domain_scores_codex":[0.9970589,0.001632954,0.0001607499,0.0004369367,0.0003279787,0.0003826646],"domain_scores_gemma":[0.9961053,0.001766152,0.0005944474,0.0004593888,0.0004841551,0.0005905682],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"observational","study_design_scores_codex":[0.00002124661,0.00003638302,0.01510989,0.0002592826,0.00002579819,0.0002480301,0.01014938,0.0002585586,0.0001082474,0.9018859,0.02425436,0.04764285],"study_design_scores_gemma":[0.00001174808,0.00006592568,0.0237885,0.0007821929,0.0000270012,0.0009445224,0.01682109,0.0003587513,0.00007820891,0.4952329,0.4618595,0.00002966036],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.1170681,0.0658189,0.04894243,0.3543846,0.00648639,0.0005244262,0.005348862,0.0003998434,0.4010264],"genre_scores_gemma":[0.9167161,0.03254584,0.0112084,0.02646111,0.00230904,0.0004834111,0.001348783,0.00005771441,0.008869673],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.006895337,"threshold_uncertainty_score":0.02306718,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.3884429019432206,"score_gpt":0.5435800527293629,"score_spread":0.1551371507861423,"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."}}