{"id":"W2114162585","doi":"10.4141/cjas08041","title":"Comparison of techniques for estimation offorage dry matter intake bygrazing beef cattle","year":2008,"lang":"en","type":"article","venue":"Canadian Journal of Animal Science","topic":"Ruminant Nutrition and Digestive Physiology","field":"Agricultural and Biological Sciences","cited_by":43,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Grazing; Dry matter; Forage; Net energy; Pasture; Animal science; Beef cattle; Cattle grazing; Biology; Mathematics; Agronomy","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002765757,0.0006621529,0.000608829,0.002428658,0.000233592,0.0005663116,0.0006574096,0.0005010415,0.0003849781],"category_scores_gemma":[0.006395001,0.0004800123,0.0005245698,0.001286119,0.0001808933,0.0005316054,0.000391058,0.0003506451,0.0001883589],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000388992,"about_ca_system_score_gemma":0.0003438953,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002978757,"about_ca_topic_score_gemma":0.008632356,"domain_scores_codex":[0.9976676,0.0007583823,0.0001742379,0.0003428606,0.0009652785,0.0000916715],"domain_scores_gemma":[0.995669,0.00224295,0.0006386044,0.0001759669,0.001184738,0.00008869303],"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":[0.002690023,0.0005231173,0.3764968,0.001171891,0.0011105,0.0001416963,0.000926002,0.002768368,0.1793111,0.000258239,0.0004031581,0.4341992],"study_design_scores_gemma":[0.0002199455,0.005670982,0.8458173,0.0001953978,0.0009949695,0.001713293,0.0005758359,0.03738036,0.1030459,0.0003741674,0.003819169,0.0001926238],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9053613,0.004613239,0.08749922,0.00006887309,0.00004770344,0.0002162577,0.0006196169,0.0002312981,0.001342513],"genre_scores_gemma":[0.7181939,0.004293611,0.2742569,0.00007190463,0.0000557975,0.0004352588,0.001165873,0.00007173518,0.001454997],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.002978757,"threshold_uncertainty_score":0.01462692,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04588182144635545,"score_gpt":0.2896891678247294,"score_spread":0.243807346378374,"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."}}