{"id":"W3153402073","doi":"10.3168/jds.2020-19584","title":"The hidden cost of disease: I. Impact of the first incidence of mastitis on production and economic indicators of primiparous dairy cows","year":2021,"lang":"en","type":"article","venue":"Journal of Dairy Science","topic":"Milk Quality and Mastitis in Dairy Cows","field":"Agricultural and Biological Sciences","cited_by":103,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Montréal; Ste. Anne's Hospital; McGill University","funders":"Agriculture and Agri-Food Canada; Ministère de l'Agriculture, des Pêcheries et de l'Alimentation; Natural Sciences and Engineering Research Council of Canada; Dairy Farmers of Canada; Fonds de recherche du Québec – Nature et technologies; Novalait","keywords":"Lactation; Mastitis; Herd; Animal science; Milk production; Cumulative incidence; Dairy cattle; Medicine; Biology; Veterinary medicine; Pregnancy; Internal medicine","routes":{"ca_aff":true,"ca_fund":true,"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":[0.001263746,0.00008787753,0.0002404057,0.00003681151,0.0002224106,0.00002335328,0.0006839022,0.00003351373,0.00004775254],"category_scores_gemma":[0.001120907,0.00002979835,0.000150135,0.0005380907,0.001347084,0.0002821096,0.0001896089,0.0001339404,3.702705e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006029639,"about_ca_system_score_gemma":0.0003471395,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001214629,"about_ca_topic_score_gemma":0.0004110109,"domain_scores_codex":[0.9984918,0.0001052763,0.0005827572,0.0001698395,0.0004991069,0.0001512489],"domain_scores_gemma":[0.9981028,0.0003234574,0.001112075,0.0001572042,0.0002046009,0.00009987809],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0006573405,0.0004779516,0.7468047,0.0001671719,0.00008466297,0.000009841012,0.001270727,0.001812768,0.171294,0.002612738,0.002604475,0.07220358],"study_design_scores_gemma":[0.0001081333,0.0004523211,0.9656383,0.0002853511,0.00002137022,0.00003254849,0.0003270392,0.00003336028,0.03204905,0.000489207,0.0005039264,0.00005933863],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9975004,0.0004529601,0.000002140829,0.00135664,0.0003660933,0.0001265441,0.00007623529,0.000001606306,0.0001174303],"genre_scores_gemma":[0.9993617,0.0004565714,0.00004027962,0.0000249458,0.00007821804,0.000001093986,6.607569e-7,6.137296e-7,0.00003592376],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2188336,"threshold_uncertainty_score":0.4963389,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01826383001288758,"score_gpt":0.2600531252253488,"score_spread":0.2417892952124613,"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."}}