{"id":"W6999262333","doi":"","title":"Combining Genotypic, Phenotypic and Pedigree Information to Analyze Functional Traits in Dairy Cattle","year":2018,"lang":"en","type":"dissertation","venue":"The Atrium (University of Guelph)","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":"","keywords":"Dairy cattle; Best linear unbiased prediction; Holstein Cattle; Heritability; Genomic information; Genomic selection; Fertility; Haplotype; SNP","routes":{"ca_aff":false,"ca_fund":false,"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":[0.002605034,0.0004916748,0.0004360122,0.001482634,0.0003067311,0.0008436362,0.0004139839,0.0002444313,0.0002880869],"category_scores_gemma":[0.002051802,0.0001752066,0.0005448255,0.001846783,0.0002672506,0.0002703216,0.00051507,0.0003516504,0.00008155548],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008533669,"about_ca_system_score_gemma":0.0009064013,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.05189186,"about_ca_topic_score_gemma":0.1182777,"domain_scores_codex":[0.9986724,0.0005280575,0.00004676568,0.0002437184,0.0003897722,0.0001192921],"domain_scores_gemma":[0.9988927,0.0005564921,0.0001827457,0.0001115151,0.0001664444,0.00009004967],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0005487219,0.0002053486,0.8401811,0.00009487939,0.001451137,0.0001887818,0.0005760447,0.009001828,0.04891761,0.0002241491,0.0001244336,0.098486],"study_design_scores_gemma":[0.00001022469,0.0002071653,0.9903652,0.00001117041,0.0003592177,0.00008298003,0.0001241504,0.005734205,0.002659758,0.0001246009,0.0003024644,0.00001886716],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9954363,0.0002772147,0.003671389,0.00002052867,0.000001911583,0.00001732106,0.0002710297,0.00001530825,0.0002891277],"genre_scores_gemma":[0.9819288,0.0003689968,0.0162602,0.00003471308,0.000005392537,0.00003159719,0.0009085154,0.000009940562,0.0004518024],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.05189186,"threshold_uncertainty_score":0.1031796,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.010095543098387,"score_gpt":0.2110012254307067,"score_spread":0.2009056823323197,"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."}}