{"id":"W2066667259","doi":"10.1111/j.1752-4571.2012.00280.x","title":"Understanding admixture patterns in supplemented populations: a case study combining molecular analyses and temporally explicit simulations in <scp>A</scp>tlantic salmon","year":2012,"lang":"en","type":"article","venue":"Evolutionary Applications","topic":"Fish Ecology and Management Studies","field":"Environmental Science","cited_by":38,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université Laval","funders":"Région Normandie; Office National de l’Eau et des Milieux Aquatiques; Institut National de la Recherche Agronomique","keywords":"Stocking; Biology; Biological dispersal; Hatchery; Microsatellite; Endangered species; Fish <Actinopterygii>; Ecology; Fishery; Population; Habitat; Allele; Gene; Genetics","routes":{"ca_aff":true,"ca_fund":false,"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":[0.001674292,0.0003417334,0.0003643091,0.0003840718,0.0004027124,0.0005963342,0.0006855593,0.0008218435,0.0005694304],"category_scores_gemma":[0.004569537,0.0002933368,0.0004468326,0.0005584025,0.0005070529,0.000912173,0.0004440873,0.0005822487,0.00004449972],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007850762,"about_ca_system_score_gemma":0.0006722936,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02543801,"about_ca_topic_score_gemma":0.02927279,"domain_scores_codex":[0.9997177,0.0001763566,0.00001952299,0.00004695718,0.00001523318,0.00002421999],"domain_scores_gemma":[0.9963952,0.002902284,0.0002602755,0.000213444,0.0001111665,0.0001176459],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00007203995,0.0001160507,0.04276731,0.00002542842,0.0001197973,0.0001790905,0.0001797234,0.9499804,0.001463663,0.001335625,0.00007312496,0.003687775],"study_design_scores_gemma":[0.00001183616,0.00004401995,0.005422111,0.000003455879,0.00002067899,0.00001754033,0.00008586176,0.9934242,0.0002616435,0.0006052959,0.00009498022,0.000008331197],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9943843,0.00002671975,0.005179502,0.00006432692,0.000002129883,0.000007696226,0.00005038216,0.000016581,0.0002683206],"genre_scores_gemma":[0.9945881,0.00002555468,0.005186332,0.00001537697,0.000002826489,0.00001505742,0.00006499282,0.000006433738,0.00009537915],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02543801,"threshold_uncertainty_score":0.05057991,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1031086451344771,"score_gpt":0.3352663971961864,"score_spread":0.2321577520617094,"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."}}