{"id":"W2893646186","doi":"10.1016/j.foodres.2018.09.014","title":"An economic analysis of salmonella detection in fresh produce, poultry, and eggs using whole genome sequencing technology in Canada","year":2018,"lang":"en","type":"article","venue":"Food Research International","topic":"Salmonella and Campylobacter epidemiology","field":"Agricultural and Biological Sciences","cited_by":33,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"Ministry of Health, British Columbia; Genome Canada; McGill University; World Health Organization","keywords":"Salmonella; Outbreak; Economic cost; Cost estimate; Indirect costs; Biology; Biotechnology; Business; Economics; Virology","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":[0.0008708083,0.0005119694,0.0003266135,0.002214527,0.001012402,0.001107047,0.0008454138,0.00034868,0.001112862],"category_scores_gemma":[0.002611126,0.0003041206,0.001050053,0.00338291,0.0004277052,0.0004027046,0.000520038,0.0004424459,0.00008432147],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.06503654,"about_ca_system_score_gemma":0.03478297,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9952136,"about_ca_topic_score_gemma":0.995016,"domain_scores_codex":[0.9990767,0.0001140635,0.0000374091,0.00008520856,0.0004154938,0.0002710452],"domain_scores_gemma":[0.9984617,0.0002823658,0.0002037895,0.00003186944,0.0008214338,0.0001989086],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0004760546,0.0002498513,0.8492951,0.0004943537,0.0006137996,0.0007208478,0.0003379794,0.09024517,0.001120565,0.004698526,0.005240845,0.04650681],"study_design_scores_gemma":[0.00003613851,0.0001477901,0.9273756,0.00008374959,0.0002599582,0.0001865669,0.0009918056,0.0651799,0.0007359292,0.0005154983,0.004437746,0.00004940213],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9783779,0.001957235,0.001924436,0.0007250705,0.00001466991,0.0001584397,0.01163027,0.00002860302,0.005183321],"genre_scores_gemma":[0.9907402,0.001282653,0.001375895,0.00008713583,0.000004242837,0.00002781257,0.003765675,0.000007598864,0.002708713],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.06503654,"threshold_uncertainty_score":0.4718753,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07388443565719173,"score_gpt":0.3430711165136284,"score_spread":0.2691866808564367,"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."}}