{"id":"W2296083684","doi":"10.1111/1755-0998.12518","title":"Population structure of Atlantic mackerel inferred from <scp>RAD</scp>‐seq‐derived <scp>SNP</scp> markers: effects of sequence clustering parameters and hierarchical <scp>SNP</scp> selection","year":2016,"lang":"en","type":"article","venue":"Molecular Ecology Resources","topic":"Genetic diversity and population structure","field":"Biochemistry, Genetics and Molecular Biology","cited_by":82,"is_retracted":false,"has_abstract":true,"ca_institutions":"Fisheries and Oceans Canada","funders":"Fisheries and Oceans Canada; King Abdullah University of Science and Technology","keywords":"Biology; Population genomics; Population; SNP; Genetics; Locus (genetics); Single-nucleotide polymorphism; Genomics; Computational biology; Mackerel; Evolutionary biology; Genotype; Genome; Gene; Fishery; Fish <Actinopterygii>","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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.000149624,0.000422141,0.0005943924,0.0002180525,0.0001656285,0.00004151257,0.0003569658,0.0008010152,0.000008702057],"category_scores_gemma":[0.001340263,0.0003801397,0.0001887648,0.0002246596,0.000387579,0.00002343069,0.0003358131,0.0002501979,0.000003233072],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003257616,"about_ca_system_score_gemma":0.00005520815,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002576547,"about_ca_topic_score_gemma":0.0002697465,"domain_scores_codex":[0.997327,0.0005120447,0.0005373029,0.0007850169,0.0003141043,0.0005245513],"domain_scores_gemma":[0.9981635,0.0005318589,0.0005251557,0.0004363087,0.0001443661,0.000198859],"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":[0.0000298863,0.00003043854,0.2728741,0.0001316361,0.0002731421,0.00001583323,0.0004368217,0.0008052053,0.7246848,0.00002764558,0.0001832547,0.0005072233],"study_design_scores_gemma":[0.001636394,0.0005751598,0.5558699,0.0001021935,0.0002187767,0.00006092047,0.0002143544,0.0005186297,0.4387663,0.0008808998,0.001063653,0.00009282794],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9953376,0.0004774214,0.003151334,0.0000416774,0.0002527257,0.0005051428,0.0001239226,0.00003449146,0.00007565665],"genre_scores_gemma":[0.9957663,0.0001188933,0.003319674,0.0001696701,0.00008002479,0.00001167906,0.0003541584,0.00004369577,0.0001358787],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2859185,"threshold_uncertainty_score":0.9998651,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.00859149533769864,"score_gpt":0.2217881552580438,"score_spread":0.2131966599203451,"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."}}