{"id":"W2334232668","doi":"10.1017/s0950268813002781","title":"Weather and livestock risk factors for <i>Escherichia coli</i> O157 human infection in Alberta, Canada","year":2014,"lang":"en","type":"article","venue":"Epidemiology and Infection","topic":"Animal Disease Management and Epidemiology","field":"Agricultural and Biological Sciences","cited_by":9,"is_retracted":false,"has_abstract":true,"ca_institutions":"Provincial Laboratory of Public Health; Institute of Health Economics; Alberta Health Services; EcoMetrix; Public Health Agency of Canada; Alberta Health; University of Guelph","funders":"Ontario Ministry of Agriculture, Food and Rural Affairs","keywords":"Poisson regression; Livestock; Negative binomial distribution; Covariate; Veterinary medicine; Regression analysis; Poisson distribution; Population; Statistics; Geography; Environmental health; Medicine; Mathematics; Forestry","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":[0.0003466447,0.0002047524,0.0001493036,0.0006913056,0.0007754161,0.0006852977,0.0004245755,0.0001904627,0.001406168],"category_scores_gemma":[0.0009100864,0.0001364194,0.0002057079,0.001288992,0.0004158859,0.0001762369,0.0002954595,0.0002744691,0.00008723565],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00661854,"about_ca_system_score_gemma":0.007432815,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9877425,"about_ca_topic_score_gemma":0.9924509,"domain_scores_codex":[0.9997593,0.00003257017,0.00001266917,0.00002958926,0.00008861261,0.00007733824],"domain_scores_gemma":[0.9993464,0.00008487248,0.0001602956,0.00001885878,0.0002161977,0.0001732829],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0000549964,0.00001987174,0.995639,0.00001114744,0.0000233048,0.00007465137,0.0001694938,0.0003078828,0.0002139535,0.00006754997,0.0003581692,0.003060042],"study_design_scores_gemma":[0.000001696193,0.000009726703,0.9989663,0.000008129382,0.00001000295,0.00003023049,0.0003808443,0.000278835,0.00002371427,0.00001568659,0.0002722101,0.000002619227],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9965695,0.0005933362,0.0001405825,0.0001843203,0.000008336123,0.00001018854,0.0006811247,0.000009618997,0.001802905],"genre_scores_gemma":[0.9984733,0.0003576676,0.0001396779,0.00003511394,0.000004386738,0.000002462392,0.0003594575,0.000001864625,0.0006260382],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01225746,"threshold_uncertainty_score":0.04802114,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02643076204713508,"score_gpt":0.2526895760854573,"score_spread":0.2262588140383222,"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."}}