{"id":"W2597947163","doi":"10.1371/journal.pone.0174749","title":"Mapping global biodiversity connections with DNA barcodes: Lepidoptera of Pakistan","year":2017,"lang":"en","type":"article","venue":"PLoS ONE","topic":"Lepidoptera: Biology and Taxonomy","field":"Biochemistry, Genetics and Molecular Biology","cited_by":71,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Guelph","funders":"Canada First Research Excellence Fund; Higher Education Commision, Pakistan; International Development Research Centre; Government of Canada; Genome Canada; Ontario Genomics; Ontario Genomics Institute","keywords":"DNA barcoding; Barcode; Lepidoptera genitalia; Taxon; Biodiversity; Bin; Mitochondrial DNA; Biology; Geography; Identification (biology); Zoology; Evolutionary biology; Genealogy; Ecology; Genetics; History; Gene; Algorithm; Mathematics; Computer science","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":[0.0001595843,0.0001852515,0.00009419735,0.002604359,0.0004856731,0.0004263594,0.0001719643,0.0001322082,0.001941233],"category_scores_gemma":[0.0005733729,0.0001174907,0.0001192777,0.003166266,0.0003592717,0.0004554502,0.0006005853,0.0002287724,0.0003362306],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004567761,"about_ca_system_score_gemma":0.0005661511,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02095301,"about_ca_topic_score_gemma":0.02203396,"domain_scores_codex":[0.9998254,0.00001618877,0.00001450687,0.00004886441,0.00005273736,0.00004236733],"domain_scores_gemma":[0.9994107,0.00007545356,0.0002914783,0.0000278119,0.000137141,0.00005728884],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00008647386,0.00003368418,0.9551069,0.000120372,0.00004059594,0.0003004421,0.001676518,0.0002555779,0.006228152,0.0003301634,0.0006765371,0.03514464],"study_design_scores_gemma":[0.000003029527,0.00003275861,0.9961724,0.00001462052,0.000009581952,0.000257958,0.001347412,0.0001810567,0.0004493032,0.00005207544,0.001474145,0.000005646267],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.993879,0.0001252065,0.0004028942,0.00003335706,0.000003799458,0.00002297649,0.002319083,0.000009701535,0.003203998],"genre_scores_gemma":[0.9977131,0.0001025554,0.0007029246,0.00001004349,0.000002747299,0.00001233645,0.001197065,0.000001943506,0.0002572329],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02095301,"threshold_uncertainty_score":0.0416621,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03625263564666868,"score_gpt":0.2405893811444537,"score_spread":0.204336745497785,"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."}}