{"id":"W2769946796","doi":"10.1016/j.anifeedsci.2017.11.013","title":"Effects of feeding canola meal or soy expeller at two dietary net energy levels on growth performance, dressing and carcass characteristics of barrows and gilts","year":2017,"lang":"en","type":"article","venue":"Animal Feed Science and Technology","topic":"Animal Nutrition and Physiology","field":"Agricultural and Biological Sciences","cited_by":14,"is_retracted":false,"has_abstract":false,"ca_institutions":"Alberta Ministry of Agriculture and Forestry","funders":"Agriculture and Agri-Food Canada; Canola Council of Canada","keywords":"Canola; Meal; Animal science; Net energy; Soybean meal; Feed conversion ratio; Chemistry; Factorial experiment; Energy density; Food science; Body weight; Biology; Mathematics","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":[0.0001297397,0.0001311417,0.0002844332,0.00006736959,0.0007438636,0.00003798816,0.0002738007,0.0001210033,0.000009870415],"category_scores_gemma":[0.0001392681,0.0000589036,0.00001707569,0.0002039724,0.001860731,0.0002004234,0.0003617784,0.00009677982,4.594428e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001231436,"about_ca_system_score_gemma":0.00001717825,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002701229,"about_ca_topic_score_gemma":0.0001591199,"domain_scores_codex":[0.9990491,0.00001797844,0.0001738075,0.0003352572,0.0001505444,0.0002733656],"domain_scores_gemma":[0.9994307,0.0001127436,0.0001863434,0.00006648171,0.0001237935,0.000079955],"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":[0.0001709025,0.00002629724,0.03090794,0.00003228826,0.00000446518,0.000004589736,0.00004136621,8.350381e-9,0.9447471,0.001704633,0.00001901151,0.02234144],"study_design_scores_gemma":[0.0003121577,0.001777212,0.8271732,0.00006908658,0.000009801921,0.00002724885,0.0001185833,0.0001303659,0.1697497,0.0003700674,0.0001386221,0.0001240017],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9988074,0.0001339865,2.333649e-7,0.0006825377,0.00004557825,0.00007680979,0.00001409715,0.00001893509,0.0002204023],"genre_scores_gemma":[0.9993914,0.000383184,0.00004186746,0.00009426805,0.00004407752,0.000005244068,0.000001741365,0.000001156795,0.00003701465],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.7962652,"threshold_uncertainty_score":0.6855941,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02567293779828748,"score_gpt":0.2439280925502502,"score_spread":0.2182551547519627,"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."}}