{"id":"W2033485847","doi":"10.1371/journal.pone.0013782","title":"Laboratory Mouse Models for the Human Genome-Wide Associations","year":2010,"lang":"en","type":"article","venue":"PLoS ONE","topic":"Genetic Associations and Epidemiology","field":"Biochemistry, Genetics and Molecular Biology","cited_by":26,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"National Center for Research Resources; Canadian Institutes of Health Research; Kidney Foundation of Canada; National Institutes of Health; Canadian Society of Nephrology; Tufts Medical Center; Pfizer","keywords":"Phenotype; Gene; Biology; Genome-wide association study; Gene knockout; Genome; Genetics; Human genome; Computational biology; In silico; Concordance; Model organism; Laboratory mouse; Gene prediction; Genotype; Single-nucleotide polymorphism","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"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":[0.004220034,0.001336062,0.00122535,0.005604511,0.0009591847,0.001231851,0.001466746,0.001091047,0.01724477],"category_scores_gemma":[0.002458868,0.000910243,0.001702953,0.002428966,0.0008131326,0.0007699013,0.001973572,0.002305832,0.003092144],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005076774,"about_ca_system_score_gemma":0.0007727728,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0006839145,"about_ca_topic_score_gemma":0.002003424,"domain_scores_codex":[0.9952065,0.001802637,0.0006964919,0.001205021,0.0007832556,0.0003059578],"domain_scores_gemma":[0.9963158,0.001160273,0.0007638401,0.001291243,0.0002408467,0.0002280289],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.003617015,0.001379898,0.03047302,0.001654828,0.001404694,0.002537185,0.0007303212,0.001808573,0.8551087,0.02598487,0.01315982,0.06214107],"study_design_scores_gemma":[0.002210294,0.00906505,0.1359791,0.001285554,0.005015059,0.02573157,0.0007347879,0.01282593,0.4800359,0.01872826,0.3079098,0.0004786578],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.4761866,0.01123115,0.4318276,0.001712481,0.001122292,0.003511257,0.05074579,0.005770191,0.0178926],"genre_scores_gemma":[0.5596966,0.007822037,0.3572077,0.00173124,0.0002373369,0.01391313,0.04124109,0.002092368,0.01605863],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01724477,"threshold_uncertainty_score":0.05768955,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03833734115461744,"score_gpt":0.258254859107959,"score_spread":0.2199175179533415,"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."}}