{"id":"W3096736862","doi":"10.20944/preprints202010.0615.v1","title":"Scaling Dynamics of Human Diseases and Urbanization in Colombia","year":2020,"lang":"en","type":"preprint","venue":"Preprints.org","topic":"COVID-19 epidemiological studies","field":"Mathematics","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"Canadian Institutes of Health Research; Departamento Administrativo de Ciencia, Tecnología e Innovación (COLCIENCIAS)","keywords":"Urbanization; Geography; Human settlement; Context (archaeology); Population; Public health; Malaria; Socioeconomics; Indigenous; Distribution (mathematics); Environmental health; Economic geography; Demography; Biology; Ecology; Medicine; Immunology","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0003161001,0.0001774628,0.0002028239,0.001458876,0.0004134953,0.001354713,0.0001456647,0.0001432498,0.001927286],"category_scores_gemma":[0.002907911,0.00008955995,0.0001864018,0.001223211,0.0006274852,0.000481073,0.0005188895,0.0002302164,0.00008851748],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002154697,"about_ca_system_score_gemma":0.0004829634,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.07700058,"about_ca_topic_score_gemma":0.05915191,"domain_scores_codex":[0.9997497,0.0001050883,0.00001037285,0.00005612008,0.00003042743,0.00004831698],"domain_scores_gemma":[0.9988611,0.0004941764,0.0003479393,0.00006313486,0.0001244357,0.0001092536],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0002742745,0.0001008583,0.726521,0.0005252476,0.0001568106,0.001524691,0.006812514,0.04862359,0.003986407,0.1213913,0.008835901,0.08124738],"study_design_scores_gemma":[0.00001786651,0.00003920903,0.8917891,0.00009602462,0.00003330866,0.0004906711,0.004543026,0.06525656,0.000328587,0.02375333,0.0135949,0.00005749415],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.978746,0.002569052,0.003657245,0.00108044,0.00002238209,0.00003611961,0.0008619635,0.00007102046,0.01295578],"genre_scores_gemma":[0.9982284,0.0004921763,0.0007668556,0.00001243703,0.00001219965,0.000009220324,0.0001473938,0.000005117095,0.000326137],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.07700058,"threshold_uncertainty_score":0.1531048,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.404947230122062,"score_gpt":0.4621256701221288,"score_spread":0.05717844000006678,"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."}}