{"id":"W2021282771","doi":"10.1289/ehp.9199","title":"Tracking Patterns of Enteric Illnesses in Populations and Communities","year":2006,"lang":"en","type":"article","venue":"Environmental Health Perspectives","topic":"Fecal contamination and water quality","field":"Environmental Science","cited_by":8,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Victoria","funders":"Natural Sciences and Engineering Research Council of Canada; Ministry of Health, British Columbia","keywords":"Robustness (evolution); Environmental health; Outbreak; Government (linguistics); Public health; Population; Medicine; Data science; Business; Computer science; Biology; Pathology","routes":{"ca_aff":true,"ca_fund":true,"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":[0.002872408,0.0002810854,0.0002551433,0.002414848,0.0005031984,0.0007963466,0.0006555213,0.0005190664,0.000788705],"category_scores_gemma":[0.01099533,0.0002075472,0.0003513961,0.002983677,0.0003508493,0.0006372672,0.000939759,0.0004881562,0.000116756],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001819909,"about_ca_system_score_gemma":0.001625089,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.1729267,"about_ca_topic_score_gemma":0.2095484,"domain_scores_codex":[0.9987465,0.0004382861,0.00008492788,0.0003391283,0.0002835498,0.0001076045],"domain_scores_gemma":[0.9947622,0.002483319,0.001005951,0.0005765431,0.0009286644,0.0002432916],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00007697994,0.00009585691,0.9422234,0.0000679218,0.0001681458,0.00006789544,0.0005223361,0.01486349,0.001039515,0.0004390753,0.0006959474,0.0397395],"study_design_scores_gemma":[0.00002969445,0.0001804737,0.9194815,0.00006730367,0.0001334146,0.0001872782,0.001003102,0.07177741,0.00209482,0.001705351,0.003290578,0.00004905013],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9799904,0.0001104275,0.01345714,0.0002259904,0.000006956342,0.0001444723,0.0042461,0.0001478614,0.001670584],"genre_scores_gemma":[0.9704555,0.00009421066,0.02629632,0.00003858806,0.000004872973,0.0001090057,0.002648735,0.000008168199,0.0003444782],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1729267,"threshold_uncertainty_score":0.3438402,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03129402749172796,"score_gpt":0.2934963788196824,"score_spread":0.2622023513279545,"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."}}