{"id":"W2762672420","doi":"10.1016/j.prevetmed.2017.09.015","title":"Culling from the actors’ perspectives—Decision-making criteria for culling in Québec dairy herds enrolled in a veterinary preventive medicine program","year":2017,"lang":"en","type":"article","venue":"Preventive Veterinary Medicine","topic":"Genetic and phenotypic traits in livestock","field":"Biochemistry, Genetics and Molecular Biology","cited_by":15,"is_retracted":false,"has_abstract":false,"ca_institutions":"Valacta (Canada); Agriculture and Agri-Food Canada; McGill University; Université de Montréal","funders":"UCB Pharma; Biotechnology and Biological Sciences Research Council","keywords":"Culling; Herd; Udder; Business; Milking; Production (economics); Dairy cattle; Agricultural science; Marketing; Veterinary medicine; Animal science; Economics; Medicine; Mastitis; Biology","routes":{"ca_aff":true,"ca_fund":false,"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":[0.00392804,0.0002347991,0.0002459799,0.000984982,0.002318596,0.002505793,0.0008347836,0.001009132,0.004068352],"category_scores_gemma":[0.008251505,0.0001781925,0.0003997552,0.0007390179,0.0008096498,0.0006080055,0.0008861236,0.0009752296,0.0001745355],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.01390385,"about_ca_system_score_gemma":0.008470205,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.6797866,"about_ca_topic_score_gemma":0.8746549,"domain_scores_codex":[0.9982943,0.0006909092,0.0000693957,0.0001021286,0.0001687674,0.0006745967],"domain_scores_gemma":[0.9943628,0.002145763,0.001174428,0.00006995014,0.0008214962,0.00142549],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"qualitative","study_design_scores_codex":[0.0004141183,0.0001723027,0.9840978,0.00002865477,0.00005521519,0.0003052588,0.003784808,0.0004407245,0.0002093951,0.0003646016,0.00129289,0.008834152],"study_design_scores_gemma":[0.00003409873,0.0002050929,0.9612126,0.0002178456,0.00006407068,0.0001276233,0.02864435,0.006846874,0.0001465206,0.000352615,0.002118582,0.00002987487],"study_design_candidate":"qualitative","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9961699,0.0001968027,0.0001214662,0.001479526,0.000009700686,0.00004080186,0.00016662,0.000001591413,0.001813593],"genre_scores_gemma":[0.9990838,0.0000827775,0.0001951886,0.0001030213,0.000005603311,0.00001144799,0.00010228,9.392048e-7,0.0004149392],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3202134,"threshold_uncertainty_score":0.6441984,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04647625572292406,"score_gpt":0.3865635727635707,"score_spread":0.3400873170406466,"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."}}