{"id":"W3152208272","doi":"10.3390/genes12040524","title":"Associative Overdominance and Negative Epistasis Shape Genome-Wide Ancestry Landscape in Supplemented Fish Populations","year":2021,"lang":"en","type":"article","venue":"Genes","topic":"Genetic diversity and population structure","field":"Biochemistry, Genetics and Molecular Biology","cited_by":8,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université Laval","funders":"Natural Sciences and Engineering Research Council of Canada; Ministère des Forêts, de la Faune et des Parcs","keywords":"Overdominance; Epistasis; Biology; Fish <Actinopterygii>; Genome; Evolutionary biology; Genetics; Gene; Allele; Fishery","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004524476,0.0001973515,0.0003462678,0.0007268504,0.0004823651,0.0004810452,0.0002554354,0.0002521543,0.0009613823],"category_scores_gemma":[0.0007268864,0.0001929907,0.0002439717,0.0005306003,0.0004584306,0.0002416105,0.0007702792,0.0002398343,0.00007349379],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003320242,"about_ca_system_score_gemma":0.0002201013,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003526348,"about_ca_topic_score_gemma":0.01076654,"domain_scores_codex":[0.999666,0.0000787189,0.00002811122,0.0001454206,0.00004615005,0.00003569245],"domain_scores_gemma":[0.9996786,0.00007932958,0.0000994423,0.00005879957,0.00004285211,0.00004092867],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","study_design_scores_codex":[0.0004669401,0.00004984486,0.3240359,0.00005870036,0.0002750086,0.000205482,0.001721289,0.0007763744,0.663114,0.0004634021,0.00005075947,0.008782101],"study_design_scores_gemma":[0.000008598963,0.0001047217,0.9928134,0.000004598008,0.00007802079,0.0001396962,0.0004084845,0.001681745,0.00422828,0.0002150227,0.0003005058,0.00001701243],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9996505,0.00001899649,0.0001943905,0.000003509783,2.809392e-7,0.000001098612,0.0000271364,0.000003181585,0.0001009289],"genre_scores_gemma":[0.9993891,0.00001643341,0.0003768715,0.000009561582,7.449647e-7,0.000004220223,0.00007868869,0.000004181762,0.0001202065],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.003526348,"threshold_uncertainty_score":0.007011652,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02364124491053616,"score_gpt":0.2662971468243071,"score_spread":0.242655901913771,"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."}}