{"id":"W1967862300","doi":"10.1371/journal.pone.0002490","title":"Identifying Canadian Freshwater Fishes through DNA Barcodes","year":2008,"lang":"en","type":"article","venue":"PLoS ONE","topic":"Identification and Quantification in Food","field":"Biochemistry, Genetics and Molecular Biology","cited_by":690,"is_retracted":false,"has_abstract":true,"ca_institutions":"Dalhousie University; University of New Brunswick; Royal Ontario Museum; Ministry of Natural Resources and Wildlife; Fisheries and Oceans Canada; University of Guelph; Université Laval","funders":"Trent University; Idaho Department of Fish and Game; University of Manitoba; Ontario Genomics Institute; University of Windsor; Ontario Genomics; Genome Canada; Université Laval; Natural Sciences and Engineering Research Council of Canada; Massachusetts Department of Fish and Game","keywords":"DNA barcoding; Biology; Freshwater fish; Genetic distance; Species complex; Genetic divergence; Zoology; Context (archaeology); Mitochondrial DNA; Ecology; Fauna; Evolutionary biology; Genetic variation; Genetic diversity; Phylogenetic tree; Population; Fishery; Fish <Actinopterygii>; Gene; Genetics","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":[0.0005148476,0.000554928,0.0002596321,0.004233153,0.002315483,0.0007368462,0.001116966,0.0005775179,0.003195118],"category_scores_gemma":[0.00218068,0.0002338587,0.0003195215,0.004601772,0.001167071,0.0003826793,0.0008973739,0.0005143856,0.001048522],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.01011774,"about_ca_system_score_gemma":0.01260589,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.8880517,"about_ca_topic_score_gemma":0.9515712,"domain_scores_codex":[0.9985135,0.00003279851,0.00004518612,0.0003344149,0.0008763873,0.0001975886],"domain_scores_gemma":[0.9975433,0.0001345073,0.0004818845,0.00006756837,0.001617983,0.0001548249],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0003696333,0.00005622562,0.50809,0.001818337,0.0001547179,0.0005871071,0.006806735,0.001951598,0.2610787,0.002299753,0.009210266,0.207577],"study_design_scores_gemma":[0.00001302625,0.00008587492,0.9011331,0.0002786006,0.0001327697,0.0007619071,0.002848925,0.002250519,0.03428389,0.0004054626,0.05769992,0.0001059905],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9244415,0.003230419,0.02734092,0.0007363429,0.0001098194,0.0005085742,0.01824965,0.0005065028,0.02487625],"genre_scores_gemma":[0.9232983,0.001549628,0.0563684,0.0005017135,0.00001809557,0.0002371525,0.008832121,0.0000728489,0.009121764],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1119483,"threshold_uncertainty_score":0.2252151,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1098369733370673,"score_gpt":0.2547361704059293,"score_spread":0.144899197068862,"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."}}