{"id":"W3163191400","doi":"10.1093/tas/txab076","title":"Economic impact of digital dermatitis, foot rot, and bovine respiratory disease in feedlot cattle","year":2021,"lang":"en","type":"article","venue":"Translational Animal Science","topic":"Animal Behavior and Welfare Studies","field":"Veterinary","cited_by":15,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary","funders":"","keywords":"Feedlot; Bovine respiratory disease; Animal science; Incidence (geometry); Veterinary medicine; Beef cattle; Cumulative incidence; Biology; Animal husbandry; Animal health; Foot rot; Medicine; Internal medicine; Immunology; Agriculture; Mathematics; Cohort","routes":{"ca_aff":true,"ca_fund":false,"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":[0.001419917,0.0003056343,0.0002034873,0.001488715,0.0003251022,0.0009177772,0.0002448343,0.0002597995,0.001515877],"category_scores_gemma":[0.002291283,0.0001229868,0.0003759776,0.001435337,0.0002812387,0.0004157176,0.0004501274,0.0002486273,0.0001277637],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001437055,"about_ca_system_score_gemma":0.0003606392,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0379535,"about_ca_topic_score_gemma":0.07323972,"domain_scores_codex":[0.9986771,0.0004459379,0.00009633995,0.0001766847,0.0003641245,0.0002398232],"domain_scores_gemma":[0.9974918,0.0007317168,0.00118351,0.00008599711,0.0003024891,0.0002044578],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001047651,0.00003924796,0.9949923,0.00003164475,0.00009252208,0.00007275068,0.00003209371,0.0005413815,0.0003726254,0.00002185695,0.0001374448,0.003561228],"study_design_scores_gemma":[0.000001459664,0.00005331364,0.9988926,0.00001073027,0.0000219564,0.00005615465,0.000103659,0.0006093004,0.00006101828,0.00001206247,0.0001761855,0.000001486233],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9974837,0.0003980618,0.0001120081,0.00005564452,0.000003856025,0.000005648149,0.001384934,0.000003546981,0.0005527377],"genre_scores_gemma":[0.9982721,0.0002640062,0.000121232,0.00001847992,0.000006769752,0.000005432012,0.001144701,6.649397e-7,0.0001666503],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0379535,"threshold_uncertainty_score":0.07546514,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04984332020192789,"score_gpt":0.3426058157765827,"score_spread":0.2927624955746548,"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."}}