{"id":"W2084888286","doi":"10.2460/javma.2001.219.1369","title":"Welcome; A look at bovine welfare—what's good, what's bad, and the lessons within; Evaluating management practices for their impact on welfare; Welfare of cattle during slaughter and the prevention of nonambulatory (downer) cattle; Milking the golden cow—her comfort; Dairy heifer replacements—caring for the future; Veal calf TLC; The ethics of livestock shows— past, present, and future; Rodeo cattle's many performances","year":2001,"lang":"en","type":"article","venue":"Journal of the American Veterinary Medical Association","topic":"Animal Behavior and Welfare Studies","field":"Veterinary","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"Saskatchewan Research Council (Canada); Canadian Council on Animal Care","funders":"","keywords":"Welfare; Milking; Animal welfare; Livestock; Dairy cattle; Business; Political science; Animal science; Law; Geography; Biology","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":[0.003277111,0.00042843,0.0002753891,0.0003267048,0.001950424,0.001863509,0.0007366082,0.003401411,0.03473954],"category_scores_gemma":[0.006347265,0.0001672078,0.0002010183,0.0002115743,0.001542887,0.001808048,0.001653207,0.003048083,0.007413354],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001270586,"about_ca_system_score_gemma":0.001998136,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003779998,"about_ca_topic_score_gemma":0.02338859,"domain_scores_codex":[0.9978956,0.0009026206,0.00006748673,0.00008386229,0.0007682918,0.000282161],"domain_scores_gemma":[0.9922386,0.001206152,0.0004610204,0.0001786279,0.002863381,0.003052143],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00006215883,0.000149372,0.00233683,0.0001898088,0.000004929044,0.0003285052,0.001717053,0.00006768042,0.001374971,0.002209493,0.91156,0.07999915],"study_design_scores_gemma":[0.00001589981,0.0002306772,0.01212172,0.0004326109,0.000005078032,0.0004333352,0.005172128,0.00005937793,0.0005102507,0.001993887,0.9789926,0.00003239734],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"commentary","genre_gemma":"other","genre_scores_codex":[0.01976069,0.0083302,0.002652084,0.7521232,0.0282304,0.0002065081,0.0003450624,0.0003478661,0.1880039],"genre_scores_gemma":[0.09287285,0.01138374,0.007060211,0.1497453,0.01361346,0.0003369538,0.0004578425,0.000258364,0.7242713],"genre_candidate":"other","genre_consensus":null,"teacher_disagreement_score":0.03473954,"threshold_uncertainty_score":0.1162153,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05432313279426626,"score_gpt":0.3789584914769996,"score_spread":0.3246353586827333,"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."}}