{"id":"W4391340262","doi":"10.1101/gr.278157.123","title":"GenomeMUSter mouse genetic variation service enables multitrait, multipopulation data integration and analysis","year":2024,"lang":"en","type":"article","venue":"Genome Research","topic":"Genetic Mapping and Diversity in Plants and Animals","field":"Biochemistry, Genetics and Molecular Biology","cited_by":20,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"Oak Ridge National Laboratory; National Institute on Deafness and Other Communication Disorders; National Institutes of Health; National Cancer Institute; National Institute on Alcohol Abuse and Alcoholism; National Institute on Drug Abuse; Jackson Laboratory","keywords":"Biology; Genetics; Computational biology; Genome; Interoperation; Quantitative trait locus; Inbred strain; Evolutionary biology; Gene; Interoperability; Computer science","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":[0.009407069,0.001955081,0.002719988,0.005388719,0.001032536,0.003145121,0.003503595,0.001622106,0.02631437],"category_scores_gemma":[0.01474076,0.0016711,0.002564475,0.00548131,0.0006609981,0.002032172,0.005045361,0.002587563,0.01533061],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009822194,"about_ca_system_score_gemma":0.002978856,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005176996,"about_ca_topic_score_gemma":0.009945331,"domain_scores_codex":[0.9965172,0.000781342,0.0003649431,0.0009459361,0.001152612,0.0002378851],"domain_scores_gemma":[0.9941447,0.00223755,0.0006094016,0.001853327,0.0005347606,0.0006203256],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.002589386,0.0002940291,0.02554838,0.003594873,0.003188975,0.001499364,0.001142155,0.015214,0.05260136,0.02912528,0.7351966,0.1300055],"study_design_scores_gemma":[0.002599183,0.0004381701,0.03553935,0.0007589755,0.001145369,0.001336231,0.0004222728,0.102224,0.04984535,0.07560629,0.7293553,0.0007296021],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"methods","genre_scores_codex":[0.01059744,0.000825069,0.2182498,0.0007903934,0.0004183963,0.0004458176,0.5467268,0.2159676,0.005978796],"genre_scores_gemma":[0.04175813,0.0007977481,0.2817491,0.0009937712,0.0001514357,0.002129486,0.6268292,0.04189054,0.003700564],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.02631437,"threshold_uncertainty_score":0.08803034,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.09878888857044088,"score_gpt":0.3451100272419541,"score_spread":0.2463211386715132,"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."}}