{"id":"W1986692632","doi":"10.3897/zookeys.381.6445","title":"A cornucopia of cryptic species - a DNA barcode analysis of the gobiid fish genus Trimma (Percomorpha, Gobiiformes)","year":2014,"lang":"en","type":"article","venue":"ZooKeys","topic":"Identification and Quantification in Food","field":"Biochemistry, Genetics and Molecular Biology","cited_by":61,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Guelph; Royal Ontario Museum","funders":"Ontario Ministry of Research and Innovation; Natural Sciences and Engineering Research Council of Canada; Muséum National d'Histoire Naturelle; Commonwealth Scientific and Industrial Research Organisation; Lembaga Ilmu Pengetahuan Indonesia; Genome Canada; Ontario Genomics; University of Guelph; Centre National de la Recherche Scientifique; Ontario Genomics Institute","keywords":"Biology; DNA barcoding; Lineage (genetic); Species complex; Genetic divergence; Evolutionary biology; Zoology; Genus; Morphology (biology); Phylogenetic tree; Genetic diversity; Gene; Genetics; Population","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":[0.0003405275,0.0002290804,0.0002010281,0.001664116,0.0006471253,0.000531577,0.0002978804,0.0004962802,0.002378345],"category_scores_gemma":[0.001483414,0.0001940382,0.0001776267,0.0008054728,0.0008563545,0.0003953273,0.000962032,0.0003577646,0.0003989532],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002764203,"about_ca_system_score_gemma":0.0003399304,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002204273,"about_ca_topic_score_gemma":0.008223126,"domain_scores_codex":[0.9994909,0.00005625519,0.00004756175,0.0002284325,0.0001115149,0.00006536006],"domain_scores_gemma":[0.9988295,0.0002863249,0.0003379476,0.0001787722,0.0001842873,0.0001830649],"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":[0.0005169144,0.00006357321,0.4620841,0.0003040503,0.0001618947,0.0006026044,0.003920562,0.0002052893,0.4741893,0.001384862,0.0003109816,0.05625595],"study_design_scores_gemma":[0.00001025954,0.0001726598,0.9734127,0.00007658487,0.00009064146,0.002045141,0.001593883,0.001328104,0.0157344,0.0005389311,0.004976947,0.00001971628],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9956002,0.0004942437,0.001564436,0.00005072367,0.00001029292,0.00001515469,0.0001960412,0.00001853777,0.002050253],"genre_scores_gemma":[0.9973567,0.00008615372,0.00174257,0.00003802848,0.000004538058,0.00001240304,0.0002732703,0.000003814041,0.0004825822],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.002378345,"threshold_uncertainty_score":0.007956326,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01356905261802182,"score_gpt":0.2314013758681323,"score_spread":0.2178323232501105,"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."}}