{"id":"W2306141362","doi":"10.1111/1755-0998.12528","title":"Revisiting the ichthyodiversity of Java and Bali through <scp>DNA</scp> barcodes: taxonomic coverage, identification accuracy, cryptic diversity and identification of exotic species","year":2016,"lang":"en","type":"article","venue":"Molecular Ecology Resources","topic":"Identification and Quantification in Food","field":"Biochemistry, Genetics and Molecular Biology","cited_by":107,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Guelph","funders":"Science Foundation Ireland; Muséum National d'Histoire Naturelle; Ontario Genomics Institute; Government of Canada","keywords":"Biology; DNA barcoding; Checklist; Species complex; Java; Biodiversity; Ecology; Barcode; Taxonomic rank; Taxonomy (biology); Identification (biology); Intraspecific competition; Species richness; Global biodiversity; Species identification; Zoology; Taxon","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":[0.0005899854,0.0001952312,0.000193753,0.00203509,0.0003148354,0.0006507846,0.0002922576,0.0001566066,0.0008273638],"category_scores_gemma":[0.001335667,0.0001484774,0.0001500526,0.001883946,0.0004670232,0.0006802506,0.0006983884,0.0002460758,0.000196583],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003934066,"about_ca_system_score_gemma":0.0009687985,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02211172,"about_ca_topic_score_gemma":0.06526588,"domain_scores_codex":[0.9995798,0.00007195974,0.00007948076,0.00008184203,0.0001411794,0.00004567244],"domain_scores_gemma":[0.9988163,0.0001839144,0.0006278645,0.00006629487,0.0002290809,0.00007661329],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00006465227,0.00005197484,0.8747821,0.0003916302,0.00004092446,0.0006016803,0.004517913,0.0001409098,0.02159432,0.0001493667,0.0004026978,0.09726186],"study_design_scores_gemma":[0.000001385633,0.00003002138,0.9953077,0.00005296484,0.00001298338,0.0004115293,0.001605514,0.0002028176,0.0006441549,0.00003754051,0.001686976,0.000006304115],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9968703,0.0007195229,0.0007466429,0.0000737996,0.00001041055,0.0000246519,0.0004026229,0.0000136791,0.001138286],"genre_scores_gemma":[0.9947081,0.0008023526,0.0030353,0.00006413148,0.000009883595,0.00002914593,0.0007624192,0.00001043065,0.0005783499],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02211172,"threshold_uncertainty_score":0.043966,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02354649765081056,"score_gpt":0.2342200362063648,"score_spread":0.2106735385555542,"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."}}