{"id":"W2523266736","doi":"10.1111/asj.12683","title":"Leather quality of beefalo‐Nellore cattle in different production systems","year":2016,"lang":"en","type":"article","venue":"Animal Science Journal","topic":"Meat and Animal Product Quality","field":"Agricultural and Biological Sciences","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"Agriculture and Agri-Food Canada","funders":"Fundação de Apoio ao Desenvolvimento do Ensino, Ciência e Tecnologia do Estado de Mato Grosso do Sul","keywords":"Production system (computer science); Silage; Pasture; Animal science; Brachiaria; Carcass weight; Biology; Body weight; Beef cattle; Significant difference; Agronomy; Forage; Medicine; Production (economics)","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":[0.0004973651,0.00029412,0.0002994156,0.00046758,0.0003783455,0.0005487091,0.0001250204,0.0002165238,0.0008374215],"category_scores_gemma":[0.0004464643,0.0002040381,0.0002409145,0.0002418352,0.0003611761,0.0002451289,0.000302655,0.000231595,0.0001899855],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006844508,"about_ca_system_score_gemma":0.0002105927,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007494866,"about_ca_topic_score_gemma":0.02658722,"domain_scores_codex":[0.9996346,0.00008225427,0.00002035521,0.00008004728,0.00007391876,0.0001087685],"domain_scores_gemma":[0.9993793,0.00007857513,0.0002102435,0.00002488382,0.00007225342,0.0002347319],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.008227612,0.001052501,0.6828569,0.00009345997,0.0002362573,0.0005363447,0.001368544,0.0001870468,0.293276,0.0000349347,0.00008578986,0.01204476],"study_design_scores_gemma":[0.0000110494,0.001385162,0.9964239,0.000002415648,0.00002039284,0.0000926203,0.0002534786,0.0000498892,0.001660002,0.000003527515,0.00009416251,0.000003375313],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9998468,0.00002430828,0.00001903664,0.00000209177,5.148108e-7,0.00000207806,0.0000172719,4.350197e-7,0.00008731569],"genre_scores_gemma":[0.999022,0.00005091489,0.00012458,0.00001601989,0.000002260019,0.000005236822,0.0001823459,0.000001735645,0.0005948613],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.007494866,"threshold_uncertainty_score":0.01490247,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08468376078082268,"score_gpt":0.3002148345776642,"score_spread":0.2155310737968415,"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."}}