{"id":"W4412216521","doi":"","title":"Genetic selection for lower methane emission in dairy cattle – ready for implementation?","year":2024,"lang":"en","type":"article","venue":"","topic":"Genetic and phenotypic traits in livestock","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Guelph","funders":"","keywords":"Selection (genetic algorithm); Methane; Dairy cattle; Methane emissions; Biology; Environmental science; Agricultural science; Biotechnology; Animal science; Computer science; Ecology; Artificial intelligence","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":[0.006559758,0.0007684453,0.0009082906,0.000295568,0.0003139754,0.001176945,0.00139367,0.001214729,0.0039993],"category_scores_gemma":[0.002831284,0.0001896765,0.0005034829,0.0006450926,0.001184149,0.0007609468,0.0006489896,0.001528624,0.0003358564],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007526424,"about_ca_system_score_gemma":0.001918581,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00426195,"about_ca_topic_score_gemma":0.006831376,"domain_scores_codex":[0.9981495,0.0009605816,0.0000996903,0.0002524442,0.0003303367,0.00020748],"domain_scores_gemma":[0.9983225,0.0006610059,0.0002502137,0.0002108934,0.0002451577,0.0003102044],"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":[0.01569756,0.002160203,0.1410172,0.0008347397,0.003089943,0.0009347022,0.0004993991,0.006359192,0.3669241,0.02585097,0.006731769,0.4299004],"study_design_scores_gemma":[0.004698694,0.01303742,0.7916827,0.001331544,0.003298421,0.001134975,0.003246353,0.01269599,0.0605995,0.03945215,0.06841442,0.0004078321],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9358358,0.007346583,0.01409057,0.03535086,0.0006076592,0.00008985436,0.0006156638,0.0002167634,0.005846215],"genre_scores_gemma":[0.9673572,0.004935605,0.01710009,0.005469749,0.0004982375,0.0001256002,0.00075114,0.0001091079,0.003653259],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.006559758,"threshold_uncertainty_score":0.03469175,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01980100215251344,"score_gpt":0.3332328090570938,"score_spread":0.3134318069045803,"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."}}