{"id":"W1873755177","doi":"10.1139/cjfas-2015-0016","title":"Life-history characteristics and landscape attributes as drivers of genetic variation, gene flow, and fine-scale population structure in northern Dolly Varden (<i>Salvelinus malma malma</i>) in Canada","year":2015,"lang":"en","type":"article","venue":"Canadian Journal of Fisheries and Aquatic Sciences","topic":"Fish Ecology and Management Studies","field":"Environmental Science","cited_by":31,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia; Fisheries and Oceans Canada","funders":"Fisheries Joint Management Committee","keywords":"Salvelinus; Fish migration; Sympatric speciation; Ecology; Population; Biology; Arctic; Genetic structure; Genetic variation; Habitat; Geography; Fishery; Demography; Trout","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":true,"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":[0.0002866553,0.000129796,0.0001847904,0.0005868708,0.001082574,0.0005403746,0.0003473168,0.0001786044,0.0005297182],"category_scores_gemma":[0.000669206,0.0001134614,0.0001601649,0.0007258007,0.0006492606,0.0001601831,0.0003255426,0.0001869907,0.00005311235],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.004251503,"about_ca_system_score_gemma":0.002482618,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.8944941,"about_ca_topic_score_gemma":0.9737332,"domain_scores_codex":[0.9997974,0.00002612159,0.00000838439,0.00006625698,0.00004064106,0.00006130522],"domain_scores_gemma":[0.9996101,0.00005421812,0.00008149985,0.00001662103,0.0001208265,0.0001167493],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00005236847,0.00001330778,0.9904062,0.0000102031,0.00005128338,0.0000945573,0.001854648,0.0003629863,0.003296799,0.00008399585,0.0001367573,0.003636888],"study_design_scores_gemma":[9.001008e-7,0.000004082103,0.9989175,0.000002733442,0.000006367238,0.00002158273,0.0006499115,0.000179098,0.00005233655,0.00001132645,0.0001515516,0.000002505152],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9997228,0.0000380608,0.00003218057,0.000009145959,4.291523e-7,0.000001151964,0.00006473471,7.93931e-7,0.0001307205],"genre_scores_gemma":[0.9996152,0.00003012167,0.00007098127,0.000006411183,4.867865e-7,0.000001687638,0.0001341804,0.000001138854,0.0001397611],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1055059,"threshold_uncertainty_score":0.2122545,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009143155976686348,"score_gpt":0.1667742396268106,"score_spread":0.1576310836501243,"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."}}