{"id":"W3046971939","doi":"10.3168/jds.2020-18177","title":"A survey of management practices that influence calf welfare and an estimation of the annual calf mortality risk in pastured dairy herds in Uruguay","year":2020,"lang":"en","type":"article","venue":"Journal of Dairy Science","topic":"Animal health and immunology","field":"Veterinary","cited_by":39,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Prince Edward Island","funders":"Instituto Nacional de Tecnología Agropecuaria; Instituto Nacional de Investigacion Agropecuaria, Uruguay; Universidad de la República Uruguay; Agencia Nacional de Investigación e Innovación; Instituto Nacional de Investigación Agropecuaria; Instituto Nacional de Investigación y Tecnología Agraria y Alimentaria","keywords":"Milking; Herd; Weaning; Welfare; Population; Animal science; Veterinary medicine; Medicine; Demography; Biology; Environmental health","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003093351,0.00008862232,0.0002554041,0.000138471,0.00009282033,0.00001825482,0.0005068457,0.00005033237,0.000005447943],"category_scores_gemma":[0.001172068,0.00006192547,0.00002614953,0.0007863847,0.0004319049,0.001381352,0.0001886643,0.0003495709,3.792827e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005383016,"about_ca_system_score_gemma":0.0002083822,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003948449,"about_ca_topic_score_gemma":0.0009547273,"domain_scores_codex":[0.9979911,0.0005532116,0.0006107113,0.0001863852,0.0004619159,0.0001966835],"domain_scores_gemma":[0.9979398,0.0001274542,0.001458867,0.0001875032,0.0001894027,0.00009696859],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.001095786,0.0001119256,0.9907526,0.0001124983,0.00000995275,0.00003370042,0.003048732,0.0004084655,0.0007877477,0.00004310883,0.000007874162,0.003587602],"study_design_scores_gemma":[0.0005125289,0.001368669,0.9918485,0.0000715272,0.0000115609,0.00003146827,0.002633219,0.00332349,0.00007864927,0.0000455498,0.00001884342,0.00005593507],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9985946,0.0003083228,0.00006527164,0.0006750663,0.00008900701,0.0001671577,0.00004230543,0.000002503195,0.00005576409],"genre_scores_gemma":[0.9993185,0.00007435301,0.0004993945,0.00009258041,0.00000835535,0.000001353739,7.249108e-7,0.000003378012,0.000001323355],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.003531667,"threshold_uncertainty_score":0.59689,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07994205178330023,"score_gpt":0.3931410368349463,"score_spread":0.3131989850516461,"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."}}