{"id":"W2089984240","doi":"10.1016/j.tvjl.2010.04.007","title":"Metabolic predictors of post-partum disease and culling risk in dairy cattle","year":2010,"lang":"en","type":"article","venue":"The Veterinary Journal","topic":"Reproductive Physiology in Livestock","field":"Agricultural and Biological Sciences","cited_by":241,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Guelph","funders":"","keywords":"Ketosis; NEFA; Ice calving; Culling; Abomasum; Medicine; Animal science; Dairy cattle; Herd; Metritis; Odds ratio; Mastitis; Endocrinology; Internal medicine; Lactation; Pregnancy; Biology; Rumen; Food science; Diabetes mellitus; Insulin","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":[0.0003814426,0.00007847521,0.0001207503,0.00001349514,0.0001857258,0.00001684497,0.000211849,0.00002926414,0.00006525468],"category_scores_gemma":[0.0001433847,0.00002418158,0.00004923088,0.00009490205,0.0002215153,0.0001215796,0.00008957446,0.000373278,0.000003101101],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000002864158,"about_ca_system_score_gemma":0.000008618382,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00004969265,"about_ca_topic_score_gemma":0.000006911462,"domain_scores_codex":[0.9992884,0.0001809666,0.0001601719,0.000137333,0.00008966102,0.0001434659],"domain_scores_gemma":[0.9995375,0.0001278482,0.0001306486,0.00007247321,0.00004522149,0.00008630567],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","study_design_scores_codex":[0.0001191832,0.00005284196,0.08124713,0.000002263513,0.00001818495,0.000006808269,0.0002192552,0.00002138179,0.9154482,0.00004649403,0.00003497648,0.002783252],"study_design_scores_gemma":[0.00007259105,0.0005550073,0.9958608,0.000008313717,0.00001894572,0.0001369174,0.0001261828,0.00001486947,0.0005812259,0.001808049,0.0007610088,0.00005610188],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9980354,0.0005961831,3.656936e-7,0.0008706598,0.0003569285,0.00008492123,0.0000232875,0.000006950188,0.00002531538],"genre_scores_gemma":[0.9990867,0.0002322225,0.00004993777,0.00002448967,0.0005779677,0.000003881765,0.000002473162,7.591634e-7,0.00002154036],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.914867,"threshold_uncertainty_score":0.1621728,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0194880818198137,"score_gpt":0.2430900260067975,"score_spread":0.2236019441869838,"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."}}