{"id":"W4323656789","doi":"10.35172/rvz.2023.v30.1052","title":"BIOMASS SORGHUM SILAGES WITH SUGARCANE","year":2023,"lang":"en","type":"article","venue":"Veterinária e Zootecnia","topic":"Ruminant Nutrition and Digestive Physiology","field":"Agricultural and Biological Sciences","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"Universidade Federal de Lavras; Universidade Federal de Viçosa","keywords":"Silage; Sorghum; Dry matter; Biomass (ecology); Agronomy; Neutral Detergent Fiber; Forage; Hemicellulose; Sweet sorghum; Fermentation; Lignin; Completely randomized design; Organic matter; Biology; Animal science; Food science; Botany","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":[0.00008972966,0.0001446937,0.0001659322,0.00002541003,0.0001653516,0.00004296273,0.0001920893,0.00007564793,0.0004839219],"category_scores_gemma":[0.0000191003,0.0000499048,0.00005692951,0.0006212256,0.0001028636,0.00007658872,0.00007735491,0.00007039552,0.0007616401],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001062232,"about_ca_system_score_gemma":0.000005123545,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001323583,"about_ca_topic_score_gemma":0.0001180398,"domain_scores_codex":[0.9990281,0.00005262911,0.0001274843,0.0003027039,0.0001366508,0.0003524613],"domain_scores_gemma":[0.9996276,0.0001157049,0.0000471939,0.0000682245,0.00004131108,0.00009988653],"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":[0.00008497191,0.00003509524,0.002460257,0.000007823656,0.000008678877,0.00004962184,0.00002015654,0.00000102653,0.9866411,0.0002324667,0.002783194,0.007675621],"study_design_scores_gemma":[0.0004071534,0.001374224,0.7917951,0.00003503874,0.000009523873,0.00004762529,0.000246959,0.00004642083,0.02912883,0.0009547634,0.1755751,0.0003792483],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9954619,0.00002691723,0.000002825324,0.002662478,0.0001191691,0.0001316405,0.00005377781,0.0003690819,0.001172141],"genre_scores_gemma":[0.9987164,0.00004543301,0.00004751546,0.0001681134,0.0001915969,0.0000301864,0.0001430253,0.000001702543,0.0006560165],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9575123,"threshold_uncertainty_score":0.9789597,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02675398825461465,"score_gpt":0.2276196324562252,"score_spread":0.2008656442016106,"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."}}