{"id":"W2100157930","doi":"10.1098/rstb.2005.1715","title":"Wedding biodiversity inventory of a large and complex Lepidoptera fauna with DNA barcoding","year":2005,"lang":"en","type":"article","venue":"Philosophical Transactions of the Royal Society B Biological Sciences","topic":"Lepidoptera: Biology and Taxonomy","field":"Biochemistry, Genetics and Molecular Biology","cited_by":341,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Guelph","funders":"Natural Sciences and Engineering Research Council of Canada; Canada Research Chairs; Guanacaste Dry Forest Conservation Fund; Forest Conservation Fund; Ontario Innovation Trust; Gordon and Betty Moore Foundation; Smithsonian Institution; Wege Foundation; National Science Foundation","keywords":"DNA barcoding; Barcode; Biology; Biodiversity; Taxonomy (biology); Ecology; Species complex; Lepidoptera genitalia; Biota; Phylogenetic tree","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003835377,0.0001246848,0.0001851729,0.00001344018,0.0004132645,0.000008309458,0.0003210299,0.0001685488,0.00006275217],"category_scores_gemma":[0.00002718712,0.00006918527,0.0002074251,0.0001338261,0.001849846,0.000009071867,0.0000740319,0.0001462577,0.000001194122],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000009962061,"about_ca_system_score_gemma":0.00002621113,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0000198783,"about_ca_topic_score_gemma":0.000006446502,"domain_scores_codex":[0.9990764,0.0001033588,0.000183575,0.0003040472,0.0001135928,0.0002190069],"domain_scores_gemma":[0.9996022,0.00005608143,0.0001029338,0.0001332329,0.00003941372,0.00006616191],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.000676429,0.001732273,0.897585,0.0001533452,0.0008534532,0.000001252962,0.0008753467,0.002830029,0.06654725,0.005914613,0.0002747756,0.02255626],"study_design_scores_gemma":[0.0179689,0.02384467,0.3362664,0.0008628516,0.001311546,0.0001527408,0.006435233,0.0466367,0.3649518,0.02237388,0.1727785,0.006416694],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9875053,0.0002047859,0.004202812,0.005589162,0.00004993225,0.0001486864,0.00004915623,0.00001056004,0.002239658],"genre_scores_gemma":[0.9973819,0.00008118504,0.001933501,0.0005032643,0.0000769499,0.000004970163,0.000005475474,0.000001676554,0.00001104081],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5613186,"threshold_uncertainty_score":0.6815833,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04758165176415463,"score_gpt":0.259909391298533,"score_spread":0.2123277395343783,"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."}}