{"id":"W4414366043","doi":"10.3168/jds.2025-26715","title":"Genotype imputation accuracy of X chromosome variants in Holstein cattle based on different software and imputation strategies","year":2025,"lang":"en","type":"article","venue":"Journal of Dairy Science","topic":"Genetic and phenotypic traits in livestock","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Guelph","funders":"Agriculture and Agri-Food Canada; Fundação de Amparo à Pesquisa do Estado da Bahia; Conselho Nacional de Desenvolvimento Científico e Tecnológico; Canadian Dairy Commission","keywords":"Imputation (statistics); Single-nucleotide polymorphism; SNP; Population; SNP genotyping; Chromosome; Pseudoautosomal region; Holstein Cattle","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":[0.01431427,0.0004892271,0.0006254665,0.0008740449,0.0005377483,0.001367392,0.00093972,0.001041806,0.004089272],"category_scores_gemma":[0.01431571,0.0003107859,0.001581633,0.00122527,0.0003760642,0.0007004865,0.0008323792,0.0007580168,0.0007946668],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005136497,"about_ca_system_score_gemma":0.001019466,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005234616,"about_ca_topic_score_gemma":0.006794857,"domain_scores_codex":[0.9956812,0.002548219,0.000265614,0.0009622988,0.0003560803,0.0001866058],"domain_scores_gemma":[0.9946831,0.003789601,0.0002573116,0.0007139881,0.0004588036,0.00009731091],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.006102977,0.0004573736,0.3857135,0.0008348864,0.005428228,0.0006562952,0.0008877494,0.2286866,0.01212745,0.006965234,0.02280119,0.3293386],"study_design_scores_gemma":[0.001086556,0.001327076,0.2626405,0.0007049908,0.002355231,0.001312183,0.0006217049,0.6693725,0.0231309,0.01793577,0.01922106,0.0002916883],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8080102,0.001363106,0.163947,0.0006150133,0.0001313471,0.0001356423,0.01640333,0.003456095,0.00593824],"genre_scores_gemma":[0.9210295,0.0002402114,0.0617141,0.0001864957,0.00001483377,0.0001439784,0.01491361,0.0002786673,0.001478595],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01431427,"threshold_uncertainty_score":0.07570207,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.00955451266557324,"score_gpt":0.2728858768804017,"score_spread":0.2633313642148285,"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."}}