{"id":"W4413422781","doi":"10.1016/j.aquaculture.2025.743096","title":"Pedigree-based genome-wide imputation using a low-density amplicon panel for the highly polymorphic Pacific oyster Crassostrea (Magallana) gigas","year":2025,"lang":"en","type":"article","venue":"Aquaculture","topic":"Marine Bivalve and Aquaculture Studies","field":"Environmental Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Vancouver Island University","funders":"Natural Sciences and Engineering Research Council of Canada; Canada Research Chairs; U.S. Department of Agriculture; Pacific States Marine Fisheries Commission","keywords":"Biology; Crassostrea; Pacific oyster; Oyster; Imputation (statistics); Amplicon; Fishery; Genetics; Zoology; Missing data; Gene; Polymerase chain reaction; Statistics","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002323738,0.0003239813,0.0002807679,0.00003856157,0.0006965331,0.0001313934,0.0003284975,0.0001545257,0.0001111432],"category_scores_gemma":[0.000108205,0.0001981055,0.0002358153,0.0003674225,0.0002028269,0.0001416014,0.0001860764,0.0002053348,0.00007879178],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001722454,"about_ca_system_score_gemma":0.00003123877,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0007502311,"about_ca_topic_score_gemma":0.001208865,"domain_scores_codex":[0.9983809,0.00006265926,0.0002872236,0.0005240066,0.000307718,0.0004374758],"domain_scores_gemma":[0.9991311,0.0002150979,0.00015278,0.0003712569,0.00005475055,0.00007504314],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0004487729,0.0004120129,0.7366865,0.0003568462,0.0006351885,0.00003508529,0.003617665,0.005357155,0.1522596,0.0008596142,0.09045222,0.008879272],"study_design_scores_gemma":[0.001978139,0.0001371793,0.8627638,0.00010648,0.0005462284,0.00001095489,0.001864384,0.006112428,0.005327863,0.001647512,0.1186583,0.000846768],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9515554,0.0005313015,0.01900627,0.01695142,0.0004341757,0.002066545,0.0001173165,0.0002051007,0.009132424],"genre_scores_gemma":[0.9921147,0.00002053188,0.0006795576,0.002094248,0.0001520709,0.0000661836,0.00009213058,0.00001952721,0.004761109],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1469318,"threshold_uncertainty_score":0.8078509,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01851979056700224,"score_gpt":0.2462036006807446,"score_spread":0.2276838101137424,"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."}}