{"id":"W4362589197","doi":"10.3390/vetsci10040268","title":"Development of a Nomogram to Estimate the 60-Day Probability of Death or Culling Due to Severe Clinical Mastitis in Dairy Cows at First Veterinary Clinical Evaluation","year":2023,"lang":"en","type":"article","venue":"Veterinary Sciences","topic":"Milk Quality and Mastitis in Dairy Cows","field":"Agricultural and Biological Sciences","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Montréal","funders":"","keywords":"Culling; Mastitis; Nomogram; Veterinary medicine; Dairy cattle; Medicine; Biology; Animal science; Herd; Internal medicine; Pathology","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":[0.01258446,0.0001773451,0.0004241844,0.00005153827,0.0004344373,0.00003907398,0.0008292123,0.0001139555,0.0003008903],"category_scores_gemma":[0.00173563,0.00007079469,0.0001272468,0.001401749,0.0004203611,0.000154978,0.0008824456,0.0001344258,0.00005812104],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006180491,"about_ca_system_score_gemma":0.0001358095,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001557598,"about_ca_topic_score_gemma":0.003841861,"domain_scores_codex":[0.996206,0.0008046055,0.001247113,0.0006652337,0.0006755101,0.000401491],"domain_scores_gemma":[0.9975041,0.001803582,0.000234393,0.0001734111,0.00012007,0.0001644782],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.001500689,0.0008809859,0.1829176,0.0002336242,0.00003890209,0.000169097,0.005427879,0.004435285,0.01111219,0.000179539,0.001067516,0.7920367],"study_design_scores_gemma":[0.0002545519,0.004794986,0.9684803,0.0002945935,0.00001018586,0.000048937,0.0006367894,0.003435317,0.0001216904,0.000325835,0.02135173,0.0002450498],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9969952,0.00002599485,0.0000349926,0.001131988,0.0005395398,0.0009499738,0.00004814842,0.00004539956,0.0002287328],"genre_scores_gemma":[0.9903671,0.00002835645,0.00915039,0.0001339145,0.00008443688,0.0001303397,0.0000213436,0.000001443412,0.00008272146],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.7917917,"threshold_uncertainty_score":0.4361546,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.3368491972697382,"score_gpt":0.4469781346398645,"score_spread":0.1101289373701263,"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."}}