{"id":"W2503331083","doi":"10.1111/mec.13795","title":"Investigating genomic and phenotypic parallelism between piscivorous and planktivorous lake trout (<i>Salvelinus namaycush</i>) ecotypes by means of<scp>RAD</scp>seq and morphometrics analyses","year":2016,"lang":"en","type":"article","venue":"Molecular Ecology","topic":"Genetic diversity and population structure","field":"Biochemistry, Genetics and Molecular Biology","cited_by":52,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université du Québec à Chicoutimi; Université Laval","funders":"Fonds de recherche du Québec – Nature et technologies; Natural Sciences and Engineering Research Council of Canada; Fonds Québécois de la Recherche sur la Nature et les Technologies","keywords":"Biology; Ecotype; Morphometrics; Salvelinus; Parallel evolution; Evolutionary biology; Ecology; Sympatric speciation; Coregonus; Reproductive isolation; Genetic divergence; Sympatry; Trout; Zoology; Genetic diversity; Phylogenetic tree; Genetics; Population; Fishery; 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":[0.0002427079,0.000208392,0.0002632002,0.0008966903,0.0004234215,0.0003907603,0.0001937936,0.0002419141,0.001223289],"category_scores_gemma":[0.0003879505,0.0001331457,0.0003371792,0.0007221365,0.0004681415,0.0001291047,0.0004682395,0.0002608825,0.0001658786],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003851692,"about_ca_system_score_gemma":0.0003353835,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01031092,"about_ca_topic_score_gemma":0.03232857,"domain_scores_codex":[0.9998086,0.00002271378,0.00001354932,0.00009137925,0.00003785988,0.00002583169],"domain_scores_gemma":[0.9997074,0.0000563847,0.0001154182,0.00001767151,0.00004641437,0.00005676724],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0005035271,0.00004117309,0.6384785,0.000106862,0.0002931808,0.0003046595,0.002004637,0.000307467,0.3508324,0.0001654483,0.0001677794,0.006794425],"study_design_scores_gemma":[0.000003872691,0.00002541643,0.9984348,0.000002358376,0.00001613966,0.00008202582,0.0001736967,0.0001770852,0.0009118549,0.00001756004,0.0001509479,0.000004312565],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9991494,0.0000349653,0.0002404616,0.000008276199,0.00000112105,0.000003473993,0.0003668196,0.00000529142,0.0001901523],"genre_scores_gemma":[0.9976563,0.00002491993,0.0006432696,0.00003341488,0.000002745569,0.00002253554,0.001231414,0.00001226293,0.0003730428],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01031092,"threshold_uncertainty_score":0.02050179,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01595597380376554,"score_gpt":0.2425816938069952,"score_spread":0.2266257200032297,"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."}}