{"id":"W4360976471","doi":"10.1093/g3journal/jkad071","title":"Design and validation of a high-density single nucleotide polymorphism array for the Eastern oyster (<i>Crassostrea virginica</i>)","year":2023,"lang":"en","type":"article","venue":"G3 Genes Genomes Genetics","topic":"Genetic and phenotypic traits in livestock","field":"Biochemistry, Genetics and Molecular Biology","cited_by":28,"is_retracted":false,"has_abstract":true,"ca_institutions":"Ministère de l’Environnement, de la Lutte contre les changements climatiques, de la Faune et des Parcs; Ministère des Ressources naturelles et des Forêts; Université Laval","funders":"Genome Atlantic; Mitacs; Genome Canada; Université Laval","keywords":"Biology; Linkage disequilibrium; Single-nucleotide polymorphism; Genetics; Crassostrea; SNP genotyping; Genotyping; Mendelian inheritance; Evolutionary biology; Oyster; Fishery; Genotype; Gene","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":true,"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":[0.001605852,0.00038431,0.000364389,0.0003453273,0.000342229,0.0005915618,0.0008306405,0.0005533482,0.0008625092],"category_scores_gemma":[0.001239289,0.0004527425,0.000363818,0.0003772387,0.0004209522,0.0001882431,0.0005144121,0.0005288976,0.0004864874],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004746115,"about_ca_system_score_gemma":0.001149878,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007009166,"about_ca_topic_score_gemma":0.01586419,"domain_scores_codex":[0.9983873,0.0002226085,0.0001355513,0.0005443406,0.0005661407,0.0001439594],"domain_scores_gemma":[0.9989946,0.0001761798,0.0001462642,0.0002190022,0.0003357626,0.0001282093],"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":[0.0001428834,0.0001095122,0.009402437,0.00006411079,0.0000337124,0.00006867453,0.00007410178,0.001542526,0.9768107,0.0002918835,0.0002824485,0.01117689],"study_design_scores_gemma":[0.000239616,0.002299451,0.1641631,0.00003795039,0.000239149,0.0006289167,0.0001363758,0.02145268,0.7914506,0.0004005026,0.01885713,0.00009450513],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7930896,0.000368789,0.1951476,0.0002835786,0.0001170256,0.002217542,0.00369346,0.001082788,0.003999645],"genre_scores_gemma":[0.6250148,0.0003868297,0.3527776,0.0008005836,0.00004730009,0.003593974,0.008763187,0.0002398042,0.008375835],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.007009166,"threshold_uncertainty_score":0.01393676,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02620809955615285,"score_gpt":0.2391170407891269,"score_spread":0.2129089412329741,"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."}}