{"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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002977708,0.0002351049,0.0002290078,0.00005543481,0.0001523765,0.00003610197,0.0003060647,0.0001607475,0.000006687164],"category_scores_gemma":[0.0000117426,0.0001961838,0.00009824795,0.0001321382,0.0001926727,0.000003371905,0.0001564477,0.00005517466,0.00001328204],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000008376699,"about_ca_system_score_gemma":0.00006665532,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001706437,"about_ca_topic_score_gemma":0.000009979576,"domain_scores_codex":[0.9986097,0.000100513,0.0003435115,0.0004359197,0.0001696586,0.0003406638],"domain_scores_gemma":[0.9988986,0.0001342699,0.0001781395,0.0005723857,0.0001267213,0.00008987443],"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":[0.000150064,0.00005985363,0.004819777,0.00005435827,0.0001868653,3.904707e-7,0.0003219094,0.008581673,0.7801344,0.00007461786,0.0005621063,0.2050539],"study_design_scores_gemma":[0.001130776,0.001122589,0.01846106,0.00001682209,0.0002205648,0.00001526866,0.0002350266,0.0004761683,0.9435813,0.002242277,0.03207007,0.0004280589],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.746888,0.04408939,0.2073599,0.0002740695,0.000492477,0.0007631585,0.00006384957,0.0000259895,0.00004313535],"genre_scores_gemma":[0.9410577,0.007092046,0.05005925,0.0001605786,0.0004868604,0.00006552725,0.0001084088,0.00006027043,0.0009093599],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2046259,"threshold_uncertainty_score":0.8000144,"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."}}