{"id":"W4386898133","doi":"10.1016/j.anscip.2023.08.018","title":"17. Nutrition for sow milk production matters","year":2023,"lang":"en","type":"article","venue":"Animal - science proceedings","topic":"Animal Behavior and Welfare Studies","field":"Veterinary","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Guelph","funders":"","keywords":"Milk production; Production (economics); Animal science; Food science; Biology; Economics; Microeconomics","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0009662883,0.0003103092,0.0002374713,0.0003213033,0.0006205278,0.00111794,0.0004360161,0.001368278,0.01532766],"category_scores_gemma":[0.00178232,0.0001412779,0.0002349866,0.0002531897,0.0006773237,0.0007875733,0.0006406723,0.0005715956,0.00275507],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007685855,"about_ca_system_score_gemma":0.001459032,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002554047,"about_ca_topic_score_gemma":0.005610614,"domain_scores_codex":[0.9997088,0.00008702691,0.00002068796,0.00006002769,0.00006961024,0.00005373227],"domain_scores_gemma":[0.9989165,0.0003934746,0.0002292273,0.00008741549,0.0001624498,0.0002109115],"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":[0.007086277,0.001099319,0.09612845,0.00186163,0.0003200022,0.003446574,0.002552505,0.0007277263,0.3011103,0.09834436,0.06669809,0.4206248],"study_design_scores_gemma":[0.0002206284,0.003185467,0.4772281,0.0009339573,0.0005560613,0.002060566,0.002567242,0.000890842,0.1060983,0.05155449,0.3546117,0.00009258746],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6035578,0.01639181,0.007492174,0.0564745,0.004441435,0.0001038704,0.002447669,0.00037614,0.3087146],"genre_scores_gemma":[0.8361524,0.009999261,0.009061264,0.0133694,0.001476098,0.0001166202,0.001042205,0.0003727823,0.12841],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01532766,"threshold_uncertainty_score":0.05127615,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08328645650183016,"score_gpt":0.3609314299414522,"score_spread":0.2776449734396221,"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."}}