{"id":"W2952431723","doi":"10.1016/j.ijfoodmicro.2019.108241","title":"Source attribution at the food sub-product level for the development of the Canadian Food Inspection Agency risk assessment model","year":2019,"lang":"en","type":"article","venue":"International Journal of Food Microbiology","topic":"Salmonella and Campylobacter epidemiology","field":"Agricultural and Biological Sciences","cited_by":10,"is_retracted":false,"has_abstract":false,"ca_institutions":"Public Health Agency of Canada; Dalhousie University; University of Manitoba; University of Guelph; Université de Montréal; Canadian Food Inspection Agency","funders":"Health Canada; Public Health Agency of Canada; Canadian Food Inspection Agency","keywords":"Food safety; Environmental health; Risk assessment; Business; Expert elicitation; Product (mathematics); Medicine; Geography; Computer science","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":[0.003634059,0.001550293,0.0006272628,0.003902723,0.001777208,0.004552648,0.003599912,0.001546052,0.08992509],"category_scores_gemma":[0.01100788,0.0007125081,0.00164155,0.004770443,0.0008321009,0.002260152,0.002025144,0.001980964,0.02263708],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.01664669,"about_ca_system_score_gemma":0.04247409,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.8533949,"about_ca_topic_score_gemma":0.8014997,"domain_scores_codex":[0.9967675,0.0003169406,0.00008926123,0.0003158899,0.002070673,0.0004397587],"domain_scores_gemma":[0.9921308,0.0004493063,0.0002099944,0.0005687834,0.006378839,0.0002622115],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0003764343,0.0002260944,0.02070579,0.0009443818,0.0002734911,0.0002863053,0.0003422788,0.08441235,0.002394152,0.1310947,0.5868632,0.1720808],"study_design_scores_gemma":[0.0001090428,0.00008873195,0.02125129,0.0007316819,0.0002104649,0.00017018,0.0006338772,0.1688543,0.003008151,0.02522562,0.7795058,0.0002108814],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.01369176,0.0009463187,0.1609134,0.005111133,0.00190751,0.002367457,0.1729341,0.00578333,0.636345],"genre_scores_gemma":[0.3242756,0.003199542,0.2101032,0.001838717,0.0002091788,0.001633349,0.1269539,0.003910106,0.3278763],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.1466051,"threshold_uncertainty_score":0.3008294,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05530272614140836,"score_gpt":0.2641585093780251,"score_spread":0.2088557832366167,"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."}}