{"id":"W2921646130","doi":"10.1371/journal.pone.0213873","title":"Opportunities for genomic selection in American mink: A simulation study","year":2019,"lang":"en","type":"article","venue":"PLoS ONE","topic":"Genetic and phenotypic traits in livestock","field":"Biochemistry, Genetics and Molecular Biology","cited_by":20,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta; University of Guelph; Dalhousie University","funders":"Mitacs","keywords":"Best linear unbiased prediction; Heritability; Selection (genetic algorithm); Mink; Statistics; Genomic selection; Missing heritability problem; Biology; Genetics; Mathematics; Computer science; Machine learning; Genotype; Genetic variants; Single-nucleotide polymorphism","routes":{"ca_aff":true,"ca_fund":true,"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":[0.001694226,0.0004475086,0.0007121972,0.000371369,0.0004552818,0.0006034221,0.0008533006,0.0007726682,0.001272009],"category_scores_gemma":[0.003299166,0.0002694298,0.0008647491,0.0005587344,0.0004826158,0.0006866368,0.0004905835,0.0005413693,0.00008518778],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00123675,"about_ca_system_score_gemma":0.0006770139,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.03179637,"about_ca_topic_score_gemma":0.02565373,"domain_scores_codex":[0.9996026,0.0002177498,0.00001272517,0.00007826509,0.00002848522,0.00006017354],"domain_scores_gemma":[0.9965648,0.002726226,0.0001905609,0.0001574021,0.0002382686,0.0001227527],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0002360729,0.0001246083,0.04724449,0.00004483746,0.00009257346,0.0001404679,0.00007972663,0.9462628,0.000898009,0.0008542524,0.0002651054,0.003757028],"study_design_scores_gemma":[0.00003986013,0.0001104064,0.01253333,0.000005558529,0.00004715616,0.00003101525,0.00008050464,0.9860532,0.0003280039,0.0005339794,0.0002223029,0.00001464077],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9966195,0.00005478743,0.002495914,0.00006831886,0.000003342906,0.00001040965,0.0001133448,0.00002223423,0.0006122282],"genre_scores_gemma":[0.9978574,0.00003419095,0.001547775,0.00001671449,0.00000179245,0.00001827152,0.0001835674,0.000005943254,0.0003342978],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.03179637,"threshold_uncertainty_score":0.06322259,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06437244470189227,"score_gpt":0.2636752803441221,"score_spread":0.1993028356422298,"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."}}