{"id":"W2008619731","doi":"10.1371/journal.pone.0051122","title":"High Potential for Using DNA from Ancient Herring Bones to Inform Modern Fisheries Management and Conservation","year":2012,"lang":"en","type":"article","venue":"PLoS ONE","topic":"Identification and Quantification in Food","field":"Biochemistry, Genetics and Molecular Biology","cited_by":67,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia; Simon Fraser University","funders":"Social Sciences and Humanities Research Council of Canada; U.S. Forest Service; Alaska Department of Transportation and Public Facilities; Hakai Institute; University of Oregon; National Science Foundation; U.S. Department of Transportation; National Geographic Society","keywords":"Pacific herring; Herring; Ancient DNA; Microsatellite; Genetic diversity; Biology; Population; Conservation genetics; Population fragmentation; Biodiversity; Ecology; Evolutionary biology; Geography; Fishery; Clupea; Genetics; Allele; Demography; Gene flow","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00008798552,0.00006591818,0.00006936342,0.00002956364,0.0001164461,0.00004415436,0.00005290464,0.0000440853,0.00001242649],"category_scores_gemma":[0.00002259556,0.00007236649,0.00001842992,0.00004062104,0.00002079957,0.0000130505,0.00005352602,0.00001599448,0.000006661127],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001029058,"about_ca_system_score_gemma":0.000006638176,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001856279,"about_ca_topic_score_gemma":0.000008909449,"domain_scores_codex":[0.9994726,0.000008068951,0.0001467687,0.0001455109,0.00009954157,0.0001275221],"domain_scores_gemma":[0.9996395,0.000003996,0.00005503207,0.0001656483,0.00008066885,0.00005511401],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.00005740083,0.0001915959,0.002106571,0.00005828065,0.0001190447,5.061526e-8,0.0002007852,0.00002301594,0.9951887,0.0009554708,0.0005260446,0.0005730654],"study_design_scores_gemma":[0.0004554867,0.00004322152,0.02983152,0.00003381004,0.0001128085,6.364315e-7,0.0002508124,0.002744654,0.96014,0.0001378284,0.006053732,0.0001955251],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9702802,0.0001327191,0.02857875,0.0004893121,0.0001095635,0.0003038285,0.00003692057,0.00001172961,0.00005692926],"genre_scores_gemma":[0.9749836,0.00001687112,0.0235847,0.0004022596,0.0001316693,0.00006170168,0.0002331104,0.00001041831,0.0005757214],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.03504871,"threshold_uncertainty_score":0.295102,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06484807708349756,"score_gpt":0.2518251032476559,"score_spread":0.1869770261641584,"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."}}