{"id":"W2768033790","doi":"10.2527/tas2017.0052","title":"Economic impacts of lameness in feedlot cattle1","year":2017,"lang":"en","type":"article","venue":"Translational Animal Science","topic":"Animal Disease Management and Epidemiology","field":"Agricultural and Biological Sciences","cited_by":35,"is_retracted":false,"has_abstract":true,"ca_institutions":"Agriculture and Agri-Food Canada; University of Calgary","funders":"Agriculture and Agri-Food Canada","keywords":"Feedlot; Lameness; Feeder cattle; Animal science; Beef cattle; Cattle Diseases; Medicine; Veterinary medicine; Livestock; Animal health; Biology; Surgery; Ecology","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004951636,0.00006760988,0.0001204395,0.00001916134,0.000284113,0.00004597064,0.0005352389,0.00002649563,0.0003446611],"category_scores_gemma":[0.00006425707,0.00002947001,0.00004339201,0.00008672001,0.0004810444,0.0004171233,0.0000559257,0.00003784619,0.0000312501],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001836446,"about_ca_system_score_gemma":0.00002830688,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001596278,"about_ca_topic_score_gemma":0.00319333,"domain_scores_codex":[0.9992235,0.0000168948,0.0001747687,0.0002235264,0.0001367915,0.000224478],"domain_scores_gemma":[0.9996616,0.00009099716,0.0001014807,0.00005208441,0.00002229404,0.00007159352],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00008010036,0.00003245828,0.7965839,0.000004104283,0.000001969529,7.865104e-7,0.00003190312,0.00005279231,0.1748227,0.02377178,0.00002549824,0.004591995],"study_design_scores_gemma":[0.00009199222,0.00008035479,0.9961554,0.000008114816,0.000002365771,4.377299e-7,0.00002346786,0.0005085144,0.0006308067,0.002209026,0.0002177671,0.00007168423],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9903339,0.0000336495,0.000001605531,0.002660367,0.00003999212,0.00007819021,0.00002411941,0.000008463291,0.006819717],"genre_scores_gemma":[0.9997991,0.00001259305,0.00004639084,0.0000556068,0.00005686854,0.000003136928,0.000005576656,3.00815e-7,0.00002047426],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1995716,"threshold_uncertainty_score":0.3773798,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04307160190729385,"score_gpt":0.2956264349092231,"score_spread":0.2525548330019293,"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."}}