{"id":"W1983110829","doi":"10.1111/1755-0998.12361","title":"One species in eight: <scp>DNA</scp> barcodes from type specimens resolve a taxonomic quagmire","year":2014,"lang":"en","type":"article","venue":"Molecular Ecology Resources","topic":"Species Distribution and Climate Change","field":"Environmental Science","cited_by":65,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Guelph","funders":"Ontario Ministry of Research and Innovation; Suomalainen Konkordia-liitto; Koneen Säätiö; Ontario Genomics Institute; Gordon and Betty Moore Foundation; Suomen Kulttuurirahasto; Helsingin Yliopiston Tiedesäätiö; Helsingin Yliopisto; Genome Canada; Ontario Ministry of Research, Innovation and Science; Ontario Genomics; Government of Canada; Ella ja Georg Ehrnroothin Säätiö","keywords":"Biology; DNA barcoding; Evolutionary biology; Computational biology; DNA; Type (biology); Genetics; Zoology; Ecology","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false,"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":[0.0009670841,0.0003520974,0.0002925882,0.001922284,0.001462693,0.0007108725,0.0006880653,0.001018262,0.009441444],"category_scores_gemma":[0.002187257,0.0003365692,0.0003187107,0.00110064,0.0007391156,0.001154938,0.001259803,0.0008600373,0.003139278],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004025328,"about_ca_system_score_gemma":0.0008273634,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003720404,"about_ca_topic_score_gemma":0.01312174,"domain_scores_codex":[0.9993836,0.00008819661,0.0001027936,0.0002186871,0.0001432658,0.00006336408],"domain_scores_gemma":[0.9985449,0.000333444,0.0003496178,0.0003132784,0.0003457336,0.0001130433],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","study_design_scores_codex":[0.0006865255,0.0001719222,0.1984994,0.001238042,0.0001479493,0.001128502,0.008180248,0.0005384908,0.4799787,0.002492515,0.007950773,0.298987],"study_design_scores_gemma":[0.00005518761,0.0004580677,0.7502045,0.0006740625,0.0001280736,0.004246393,0.003366943,0.004144696,0.05780909,0.002512561,0.176302,0.00009848722],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.938,0.0008560821,0.03538614,0.0007529141,0.0003047844,0.000615182,0.006658875,0.001129394,0.01629666],"genre_scores_gemma":[0.7657915,0.0003006314,0.2143945,0.0008564107,0.0000682296,0.0005546062,0.009441487,0.0003413283,0.008251245],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.009441444,"threshold_uncertainty_score":0.03158474,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0163150438787335,"score_gpt":0.2058810918047322,"score_spread":0.1895660479259987,"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."}}