{"id":"W2075747781","doi":"10.1371/journal.pone.0021252","title":"Pyrosequencing for Mini-Barcoding of Fresh and Old Museum Specimens","year":2011,"lang":"en","type":"article","venue":"PLoS ONE","topic":"Lepidoptera: Biology and Taxonomy","field":"Biochemistry, Genetics and Molecular Biology","cited_by":81,"is_retracted":false,"has_abstract":true,"ca_institutions":"Agriculture and Agri-Food Canada; University of Guelph","funders":"Government of Canada; Ontario Genomics; Ontario Genomics Institute; Genome Canada","keywords":"Pyrosequencing; DNA barcoding; Biology; Evolutionary biology; Zoology; Genetics; Gene","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":[0.001034288,0.0005856759,0.0006302435,0.001079989,0.000468131,0.0004753049,0.0006032651,0.0005153062,0.001472877],"category_scores_gemma":[0.002681928,0.0004460765,0.0006589825,0.000791139,0.0003318347,0.0004032833,0.0006094557,0.0008926568,0.001178849],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000187329,"about_ca_system_score_gemma":0.0004640588,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004855304,"about_ca_topic_score_gemma":0.001981638,"domain_scores_codex":[0.9991943,0.0001305791,0.00006128864,0.0002399552,0.000327866,0.00004591646],"domain_scores_gemma":[0.9990652,0.0003918442,0.0001419266,0.0001602307,0.0001879951,0.00005277159],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0001041126,0.00004779937,0.002859381,0.00024019,0.00003771266,0.0001292993,0.0002421771,0.0004245368,0.9643418,0.0004099505,0.0002224815,0.03094051],"study_design_scores_gemma":[0.00001880432,0.0006460036,0.05398096,0.00008602701,0.0001415369,0.001343174,0.0001447787,0.01064214,0.9112046,0.001774185,0.01996087,0.00005687682],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.4336016,0.002993523,0.551659,0.0001421911,0.0002275757,0.0006756099,0.004954402,0.001250767,0.004495288],"genre_scores_gemma":[0.3452255,0.001884915,0.6388852,0.0002314326,0.00006934318,0.0007814846,0.008052185,0.0003102315,0.004559766],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.001472877,"threshold_uncertainty_score":0.005469918,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07042333730799566,"score_gpt":0.2265118982699106,"score_spread":0.1560885609619149,"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."}}