{"id":"W1983199749","doi":"10.5539/sar.v3n2p1","title":"Practices to Reduce Milk Carbon Footprint on Grazing Dairy Farms in Southern Uruguay: Case Studies","year":2014,"lang":"en","type":"article","venue":"Sustainable Agriculture Research","topic":"Agriculture Sustainability and Environmental Impact","field":"Environmental Science","cited_by":27,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Instituto Nacional de Investigación Agropecuaria; United Nations Development Programme","keywords":"Grazing; Dry matter; Pasture; Stocking; Forage; Carbon footprint; Animal science; Milk production; Herd; Agronomy; Biology; Environmental science; Greenhouse gas; Ecology","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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.004163141,0.0004275246,0.0004201945,0.0002094894,0.0007563671,0.0001731641,0.0005780535,0.0002431665,0.00006952414],"category_scores_gemma":[0.003502649,0.0002673357,0.0001058098,0.001994319,0.0004200445,0.0002531769,0.00129265,0.001226023,0.0002591213],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003396567,"about_ca_system_score_gemma":0.0000380817,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01672442,"about_ca_topic_score_gemma":0.00515506,"domain_scores_codex":[0.9942232,0.001100773,0.0004243019,0.001116881,0.001275003,0.001859883],"domain_scores_gemma":[0.997924,0.0006262569,0.0001763563,0.0006500747,0.000132995,0.0004903097],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"qualitative","study_design_gemma":"qualitative","study_design_scores_codex":[0.003109046,0.008441122,0.1948823,0.003017084,0.0006181819,0.04799199,0.3432793,0.1451936,0.1172721,0.006805308,0.03067699,0.09871295],"study_design_scores_gemma":[0.00103283,0.001573275,0.03187687,0.0001243245,0.0000342853,0.0007107057,0.8935388,0.0001091068,0.006237174,0.005597357,0.0581346,0.001030665],"study_design_candidate":"qualitative","study_design_consensus":"qualitative","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9705082,0.000214768,0.00000535348,0.004265193,0.00005986034,0.001625366,0.000002817716,0.00006980809,0.02324866],"genre_scores_gemma":[0.9879068,0.00004898127,0.0001579835,0.0001528565,0.0002025149,0.0003066969,0.000006058587,0.00003024078,0.01118784],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5502595,"threshold_uncertainty_score":0.9999779,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04520927796085125,"score_gpt":0.3666022675162423,"score_spread":0.321392989555391,"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."}}