{"id":"W4250633365","doi":"10.1139/gen-2021-0013","title":"Trends in DNA Barcoding and Metabarcoding 2020","year":2021,"lang":"en","type":"article","venue":"Genome","topic":"Environmental DNA in Biodiversity Studies","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"","keywords":"DNA barcoding; Biology; Evolutionary biology; Mitochondrial DNA; Genetics; Computational biology; Gene","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":["metaresearch","bibliometrics"],"consensus_categories":[],"category_scores_codex":[0.01820017,0.0009557834,0.001511518,0.007171739,0.0006664838,0.004375516,0.002968487,0.004239501,0.01017892],"category_scores_gemma":[0.03271838,0.0006159618,0.001127962,0.009296102,0.0034216,0.005995204,0.002244682,0.003849405,0.00459459],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.004232006,"about_ca_system_score_gemma":0.008853139,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01061836,"about_ca_topic_score_gemma":0.01623705,"domain_scores_codex":[0.9940892,0.001873294,0.0006403434,0.001321377,0.001516489,0.0005591498],"domain_scores_gemma":[0.9398308,0.02129175,0.007862688,0.00193284,0.02366711,0.00541478],"domain_codex":null,"domain_gemma":"methods","domain_candidate":"methods","domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.0005866709,0.0001674541,0.02088975,0.007300865,0.0002365615,0.0001915889,0.0003550842,0.002008592,0.01484312,0.02934921,0.1106726,0.8133985],"study_design_scores_gemma":[0.00006008368,0.0003263651,0.0331251,0.003761532,0.0001874963,0.001140408,0.0008249761,0.003944648,0.006810595,0.0127862,0.9369054,0.0001271791],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"review","genre_gemma":"empirical","genre_scores_codex":[0.0288447,0.5861101,0.06972212,0.2472228,0.01377094,0.0002562024,0.009251388,0.002998337,0.04182347],"genre_scores_gemma":[0.120636,0.553194,0.1712289,0.09540009,0.01440811,0.0004472658,0.01762905,0.0009233238,0.02613335],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9928282,"threshold_uncertainty_score":0.09625286,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0176740235898724,"score_gpt":0.2134896592492418,"score_spread":0.1958156356593694,"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."}}