{"id":"W2089104593","doi":"10.1371/journal.pone.0125635","title":"The Hemiptera (Insecta) of Canada: Constructing a Reference Library of DNA Barcodes","year":2015,"lang":"en","type":"article","venue":"PLoS ONE","topic":"Fossil Insects in Amber","field":"Agricultural and Biological Sciences","cited_by":102,"is_retracted":false,"has_abstract":true,"ca_institutions":"Agriculture and Agri-Food Canada; University of Guelph","funders":"Agriculture and Agri-Food Canada; Natural Sciences and Engineering Research Council of Canada; University of Illinois at Urbana-Champaign; Genome Canada; Ontario Genomics; National Museum of Natural History; Ontario Genomics Institute","keywords":"Barcode; DNA barcoding; Workflow; Context (archaeology); Hemiptera; Identification (biology); Biology; GenBank; Taxonomy (biology); DNA sequencing; Checklist; Computer science; Library science; Computational biology; World Wide Web; Information retrieval; Zoology; Database; DNA; Ecology; Genetics","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":true,"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":[0.00214191,0.0008128068,0.0007495243,0.007288235,0.004896276,0.002877214,0.002401265,0.0007520653,0.004624379],"category_scores_gemma":[0.005045318,0.000573846,0.000826258,0.008359023,0.001114568,0.0008849672,0.001377957,0.001171161,0.002564035],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.01620837,"about_ca_system_score_gemma":0.0372728,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9240205,"about_ca_topic_score_gemma":0.9612334,"domain_scores_codex":[0.996357,0.000125442,0.0001069373,0.0007129397,0.002320932,0.0003766514],"domain_scores_gemma":[0.9964828,0.0001819454,0.0002743132,0.000246041,0.002612272,0.0002025081],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.0004291238,0.0001197143,0.08298224,0.001993212,0.0002066132,0.000645924,0.005570545,0.004295636,0.1248753,0.01172574,0.05877911,0.7083769],"study_design_scores_gemma":[0.00004950328,0.0002112304,0.3488248,0.001260744,0.000313436,0.001098521,0.002265114,0.008091052,0.03868439,0.001804023,0.5971966,0.0002006132],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.3613777,0.01928406,0.3024497,0.002371611,0.0007660582,0.004113016,0.1933092,0.01092871,0.1054],"genre_scores_gemma":[0.2325398,0.00848986,0.5819713,0.001152364,0.0001185904,0.001822689,0.1417341,0.002120004,0.03005136],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.07597953,"threshold_uncertainty_score":0.1528539,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07563019280491053,"score_gpt":0.1957319176360875,"score_spread":0.120101724831177,"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."}}