{"id":"W4392787369","doi":"10.1111/eva.13654","title":"Population genomics, life‐history tactics, and mixed‐stock subsistence fisheries in the northernmost American Atlantic salmon populations","year":2024,"lang":"en","type":"article","venue":"Evolutionary Applications","topic":"Fish Ecology and Management Studies","field":"Environmental Science","cited_by":10,"is_retracted":false,"has_abstract":true,"ca_institutions":"Ministère de l’Environnement, de la Lutte contre les changements climatiques, de la Faune et des Parcs; Parks Canada; Ministère des Ressources naturelles et des Forêts; Université Laval","funders":"Génome Québec; Ontario Genomics; Genome Canada","keywords":"Salmo; Fish migration; Biology; Fishery; Estuary; Ecology; Population; Stock (firearms); Tributary; Demographic history; Historical ecology; Population genomics; Life history theory; Geography; Genetic variation; Genomics; Habitat; Life history; Genome; Demography; 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":[0.0001809173,0.0001436622,0.0001171195,0.0004294369,0.0003235817,0.0002502686,0.0001277463,0.0001213704,0.0007175215],"category_scores_gemma":[0.0002691408,0.00008761989,0.00017233,0.0004017056,0.0002159782,0.000103295,0.0002017961,0.0001647492,0.00006674726],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002574054,"about_ca_system_score_gemma":0.0002644143,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01766602,"about_ca_topic_score_gemma":0.05467819,"domain_scores_codex":[0.9998946,0.00001510588,0.000007619352,0.00004793942,0.00001496219,0.00001969446],"domain_scores_gemma":[0.9998052,0.00003753433,0.00007165708,0.0000162958,0.00003287566,0.00003650874],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001246451,0.00003821036,0.942692,0.00002116671,0.00009702962,0.00008198344,0.000899224,0.0001374872,0.04850677,0.0001042167,0.00004755755,0.007249715],"study_design_scores_gemma":[0.00000101056,0.00001400682,0.999424,0.000001500343,0.00000855631,0.0000303853,0.0001920145,0.00008759965,0.0001612629,0.00001628691,0.00006198252,0.000001366505],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9997488,0.00002563918,0.00006360239,0.000004719081,4.353393e-7,0.000001088947,0.00004856621,7.674495e-7,0.0001064089],"genre_scores_gemma":[0.9994118,0.00002909666,0.0001815666,0.000009283635,9.52301e-7,0.000005804372,0.000167894,0.000001441913,0.0001921677],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01766602,"threshold_uncertainty_score":0.03512639,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01755450305095588,"score_gpt":0.2202018053611806,"score_spread":0.2026473023102247,"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."}}