{"id":"W2230396507","doi":"10.1371/journal.pone.0146327","title":"Identification, Discrimination, and Discovery of Species of Marine Planktonic Ostracods Using DNA Barcodes","year":2016,"lang":"en","type":"article","venue":"PLoS ONE","topic":"Environmental DNA in Biodiversity Studies","field":"Environmental Science","cited_by":33,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"National Institute of Arthritis and Musculoskeletal and Skin Diseases; Natural Environment Research Council; NOAA Ocean Exploration; Sight Research UK; National Oceanic and Atmospheric Administration; Canadian Institute for Advanced Research; Woods Hole Oceanographic Institution; Alfred P. Sloan Foundation","keywords":"DNA barcoding; Biology; Species complex; Taxon; Plankton; Zoology; Interspecific competition; Genetic divergence; Biodiversity; Mitochondrial DNA; Phylogenetic tree; Ecology; Genetic distance; Cytochrome c oxidase subunit I; Evolutionary biology; Genetic variation; Gene; Genetic diversity; Genetics","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003285492,0.0002042958,0.0001916057,0.001425361,0.0003234818,0.0002630665,0.0002586288,0.000227336,0.0004743255],"category_scores_gemma":[0.0008886708,0.0001365033,0.0001860158,0.0008132325,0.0003491089,0.0003155491,0.0003188566,0.000255693,0.0003254386],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002114591,"about_ca_system_score_gemma":0.000300347,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005554129,"about_ca_topic_score_gemma":0.01021914,"domain_scores_codex":[0.9995789,0.00004177432,0.00005679969,0.0001487366,0.0001297259,0.00004401119],"domain_scores_gemma":[0.9992194,0.0001457324,0.0003102664,0.00005375209,0.0001927558,0.00007808914],"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":[0.0001419844,0.00009623297,0.4334939,0.0001508335,0.00004305713,0.0002517414,0.001032065,0.0001760246,0.5173316,0.0001281585,0.0001454644,0.04700912],"study_design_scores_gemma":[0.000007376786,0.0002893023,0.9626501,0.00002990917,0.00003545872,0.0006838287,0.0006590288,0.001155832,0.03285269,0.00005893682,0.00155748,0.00002008535],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9955173,0.0002693459,0.00295137,0.00002138314,0.000008010576,0.00006795081,0.0004139525,0.00001636328,0.0007343081],"genre_scores_gemma":[0.9715745,0.000469964,0.02548211,0.00003930774,0.000008976697,0.00009426749,0.001473173,0.000008093854,0.0008495531],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.005554129,"threshold_uncertainty_score":0.01104361,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03686378514901965,"score_gpt":0.2092031940406806,"score_spread":0.1723394088916609,"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."}}