{"id":"W2920237588","doi":"10.1002/ece3.4985","title":"Invasion genetics from eDNA and thousands of larvae: A targeted metabarcoding assay that distinguishes species and population variation of zebra and quagga mussels","year":2019,"lang":"en","type":"article","venue":"Ecology and Evolution","topic":"Environmental DNA in Biodiversity Studies","field":"Environmental Science","cited_by":61,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Research Committee, Aristotle University of Thessaloniki; University of Toledo; National Oceanic and Atmospheric Administration; International Association for Great Lakes Research; Hudson River Foundation; Johns Hopkins University; Ontario Ministry of Natural Resources and Forestry; U.S. Geological Survey; Joint Institute for the Study of the Atmosphere and Ocean; University of Washington; River Foundation; NOAA Pacific Marine Environmental Laboratory; U.S. Environmental Protection Agency","keywords":"Biology; Zebra mussel; Dreissena; Population; Ecology; Environmental DNA; DNA barcoding; Population genetics; Invasive species; Zoology; Introduced species; Genetic diversity; Habitat; Genetic variation; Ecological genetics; Biodiversity; Mussel; Mollusca; Gene; Genetics; Bivalvia","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002042508,0.00007978624,0.0001605549,0.00002941838,0.0001219009,0.000006514902,0.00002815591,0.00008309052,0.00007458766],"category_scores_gemma":[0.00005776886,0.00007551153,0.00001101155,0.00003996002,0.0002339016,0.0001474781,0.0001986433,0.00004589335,0.000002340013],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004091539,"about_ca_system_score_gemma":9.86769e-7,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004687068,"about_ca_topic_score_gemma":0.000232039,"domain_scores_codex":[0.9994214,0.00007441873,0.0001227239,0.0002021394,0.00009129205,0.0000880604],"domain_scores_gemma":[0.9996593,0.0001254814,0.0001271796,0.00005908031,0.000003724314,0.00002525057],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00001717241,0.00001807697,0.9417973,0.00001684826,0.00001650993,1.990736e-7,0.0007511022,0.00002941558,0.05704998,0.0000599735,0.00001918045,0.0002242509],"study_design_scores_gemma":[0.0003185016,0.00008935138,0.9957389,0.00001106688,0.00005137224,0.000001479226,0.0004373289,0.0008189575,0.00163606,0.0007998337,0.0000230242,0.00007414312],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.998862,0.0006215454,0.00009012861,0.00005594502,0.00007297506,0.0001422241,0.00002590082,0.00000633993,0.0001229936],"genre_scores_gemma":[0.996854,0.0005835419,0.002477973,0.00001200307,0.000009739566,0.000001366913,0.00002025163,0.00000294459,0.00003816228],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.05541392,"threshold_uncertainty_score":0.3079271,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01246172665808685,"score_gpt":0.1917317844540288,"score_spread":0.179270057795942,"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."}}