{"id":"W3148093751","doi":"10.82308/19718","title":"Genetic selection in Canadian dairy cattle","year":2020,"lang":"en","type":"article","venue":"eScholarship@McGill (McGill)","topic":"Genetic and phenotypic traits in livestock","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Ghana Education Trust Fund; Ontario Genomics","keywords":"Dairy cattle; Selection (genetic algorithm); Business; Biotechnology; Biology; Computer science; Genetics; Artificial intelligence","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":true,"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":[0.0008829894,0.0003640752,0.0003963199,0.001364057,0.001862185,0.001178926,0.0007644439,0.000299122,0.003991357],"category_scores_gemma":[0.001656654,0.0001832275,0.0004680072,0.002758561,0.0006059585,0.0001845013,0.0003836712,0.000277299,0.0003567306],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.02466851,"about_ca_system_score_gemma":0.01857196,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9887705,"about_ca_topic_score_gemma":0.9945074,"domain_scores_codex":[0.9993265,0.0000815047,0.0000175945,0.0001665476,0.0002724704,0.0001354614],"domain_scores_gemma":[0.9992167,0.000116202,0.0000547702,0.00003061633,0.0004891326,0.00009266323],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0005900988,0.00007339298,0.8023439,0.0001948111,0.0002897742,0.0003509497,0.001997944,0.02252587,0.01534924,0.003281714,0.007491669,0.1455107],"study_design_scores_gemma":[0.00003100901,0.00007326486,0.9654405,0.00005230379,0.00009109137,0.00009229496,0.001114266,0.013098,0.001043502,0.0003877983,0.01852191,0.00005397706],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.978439,0.00146883,0.00245777,0.0005016029,0.00003185444,0.00005020746,0.003563547,0.0001409999,0.01334612],"genre_scores_gemma":[0.9811529,0.0007467773,0.004430832,0.0001313661,0.000007726229,0.00003064848,0.002666869,0.00004946058,0.01078331],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02466851,"threshold_uncertainty_score":0.1789834,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01278907378218703,"score_gpt":0.2135583966591578,"score_spread":0.2007693228769708,"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."}}