{"id":"W3108984832","doi":"10.1093/jas/skaa278.229","title":"173 Greenhouse gas emissions and land use associated with the removal of growth-enhancing technologies from backgrounding and finishing cattle in Canada: A case study","year":2020,"lang":"en","type":"article","venue":"Journal of Animal Science","topic":"Pharmacological Effects and Assays","field":"Agricultural and Biological Sciences","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Saskatchewan; Agriculture and Agri-Food Canada; University of Manitoba","funders":"","keywords":"Animal science; Greenhouse gas; Beef cattle; Environmental science; Body weight; Chemistry; Biology; Endocrinology; Ecology","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"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":[0.0003621778,0.0004039499,0.0002581098,0.0007057357,0.001523528,0.0007868598,0.0006386905,0.0004082844,0.000709894],"category_scores_gemma":[0.0005137978,0.0001582055,0.00043798,0.001509238,0.0005573016,0.0001921027,0.0002966781,0.0003159603,0.00008490848],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.02206341,"about_ca_system_score_gemma":0.01124724,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9905475,"about_ca_topic_score_gemma":0.9940491,"domain_scores_codex":[0.9996289,0.00003992923,0.000009142048,0.00004484088,0.0001376602,0.000139547],"domain_scores_gemma":[0.9995568,0.00007922859,0.00004209412,0.00001691118,0.0002279436,0.00007697832],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0005602422,0.0004487806,0.9395254,0.0001923586,0.0001939574,0.005327738,0.001706972,0.0187797,0.008926839,0.0007152969,0.0011411,0.02248163],"study_design_scores_gemma":[0.00005291327,0.0004223382,0.9606811,0.00004715539,0.0001571036,0.0008275733,0.007732957,0.02314314,0.002803214,0.0001310767,0.003952438,0.00004902094],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9978638,0.0001499898,0.0001842955,0.00004889427,0.000001198987,0.00002392517,0.0004967611,0.000006362166,0.001224736],"genre_scores_gemma":[0.9973339,0.0002703183,0.0004711612,0.00002263134,0.000001180656,0.00000726964,0.0005059667,0.000003207538,0.001384366],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02206341,"threshold_uncertainty_score":0.1600819,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0394557059437816,"score_gpt":0.245668022233035,"score_spread":0.2062123162892534,"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."}}