{"id":"W3175323757","doi":"10.1016/j.psj.2021.101362","title":"Growth performance, organ attributes, nutrient and caloric utilization in broiler chickens differing in growth rates when fed a corn-soybean meal diet with multienzyme supplement containing phytase, protease and fiber degrading enzymes","year":2021,"lang":"en","type":"article","venue":"Poultry Science","topic":"Animal Nutrition and Physiology","field":"Agricultural and Biological Sciences","cited_by":12,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Guelph","funders":"Ontario Agri-Food Innovation Alliance; Canada First Research Excellence Fund; Diagnostic Services Manitoba","keywords":"Phytase; Starter; Broiler; Amen; Gizzard; Animal science; Meal; Soybean meal; Feed conversion ratio; Food science; Biology; Nutrient; Chemistry; Protease; Body weight; Biochemistry; Enzyme; Endocrinology","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002521838,0.0004240292,0.0002912928,0.0005864749,0.0002586298,0.00030258,0.000165019,0.0004506042,0.0008204877],"category_scores_gemma":[0.0002740781,0.0003371308,0.0002457984,0.0001336279,0.0003823407,0.0003592628,0.000240603,0.0005109366,0.0003358038],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004096912,"about_ca_system_score_gemma":0.0001737952,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002972299,"about_ca_topic_score_gemma":0.005761484,"domain_scores_codex":[0.9997675,0.00003835767,0.00002305659,0.00008203808,0.00003157323,0.000057485],"domain_scores_gemma":[0.9994826,0.00009650901,0.0001143638,0.00003163408,0.00006427072,0.0002106164],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.003659537,0.0003363505,0.009209952,0.00004206871,0.00002191328,0.0001123224,0.0001661978,0.00009896047,0.9850109,0.00002032791,0.00003857666,0.001282825],"study_design_scores_gemma":[0.0002282285,0.02453525,0.6249594,0.00002955079,0.0001925419,0.0006511498,0.000867311,0.001554299,0.3457522,0.00007974087,0.001089388,0.00006097432],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9996512,0.0000657572,0.00005937157,0.000007944805,0.000002527753,0.000004389065,0.00008406521,0.000003734783,0.0001209758],"genre_scores_gemma":[0.9963936,0.0001159342,0.0004787046,0.00004058974,0.000005153929,0.00003284569,0.0004805984,0.00001011537,0.002442624],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.002972299,"threshold_uncertainty_score":0.005909979,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02976232356179858,"score_gpt":0.23030098469782,"score_spread":0.2005386611360215,"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."}}