{"id":"W1974442899","doi":"10.1002/ece3.1121","title":"Landscape variability explains spatial pattern of population structure of northern pike (<i><scp>E</scp>sox lucius</i>) in a large fluvial system","year":2014,"lang":"en","type":"article","venue":"Ecology and Evolution","topic":"Genetic diversity and population structure","field":"Biochemistry, Genetics and Molecular Biology","cited_by":17,"is_retracted":false,"has_abstract":true,"ca_institutions":"Ministère des Ressources naturelles et des Forêts; Université Laval","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Pike; Esox; Habitat; Population; Ecology; Genetic structure; Spatial variability; Environmental science; Physical geography; Genetic variation; Geography; Biology; Fishery; Fish <Actinopterygii>","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":[0.0002326059,0.00008350607,0.0001985863,0.0006525991,0.0002755149,0.0004502885,0.0001261669,0.0001712665,0.0005107321],"category_scores_gemma":[0.00074934,0.0001214961,0.0001671213,0.0005125954,0.0005343222,0.0001970101,0.0002762438,0.0001086703,0.00009218084],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005224882,"about_ca_system_score_gemma":0.0003470337,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.04124686,"about_ca_topic_score_gemma":0.09825204,"domain_scores_codex":[0.9998443,0.00003268153,0.00001351128,0.00006334126,0.00002186804,0.00002431888],"domain_scores_gemma":[0.999622,0.00008518233,0.0001486591,0.00003026686,0.00005899383,0.00005481949],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00004350088,0.00001132485,0.9899261,0.000009212963,0.00005634718,0.00006919818,0.0002802724,0.000472965,0.005975308,0.00006244432,0.00004724269,0.003046075],"study_design_scores_gemma":[7.00447e-7,0.000005647506,0.9994698,8.74665e-7,0.00000457668,0.00002012582,0.00005423108,0.0003717135,0.00003133582,0.00001522007,0.00002481429,0.000001042213],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9997782,0.00002248281,0.00006821321,0.000005676793,2.008839e-7,6.576938e-7,0.00001937179,0.000002392606,0.0001027229],"genre_scores_gemma":[0.99986,0.0000106018,0.00005219664,0.000001891568,5.026752e-7,7.539244e-7,0.00003720026,7.836539e-7,0.00003594285],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.04124686,"threshold_uncertainty_score":0.08201355,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.002934910818492926,"score_gpt":0.1839490636175447,"score_spread":0.1810141527990517,"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."}}