{"id":"W2971525712","doi":"10.1111/1755-0998.13088","title":"Enhancing DNA metabarcoding performance and applicability with bait capture enrichment and DNA from conservative ethanol","year":2019,"lang":"en","type":"article","venue":"Molecular Ecology Resources","topic":"Environmental DNA in Biodiversity Studies","field":"Environmental Science","cited_by":25,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Guelph","funders":"Agence française pour la biodiversité; Centre National de la Recherche Scientifique","keywords":"Biology; DNA; Ancient DNA; Evolutionary biology; Computational biology; Genetics","routes":{"ca_aff":true,"ca_fund":false,"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":[0.002420193,0.00114292,0.0009093432,0.001259643,0.0004722263,0.001358405,0.0007843251,0.001056114,0.001843081],"category_scores_gemma":[0.004205274,0.0006708064,0.0006286824,0.0008228598,0.0006833868,0.0008668128,0.00116119,0.0008216344,0.001931247],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003208512,"about_ca_system_score_gemma":0.0006243313,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001077412,"about_ca_topic_score_gemma":0.003936836,"domain_scores_codex":[0.9971141,0.0005944238,0.000276586,0.0009239512,0.000799726,0.000291282],"domain_scores_gemma":[0.998261,0.0006254008,0.0002863699,0.0002288717,0.0005028835,0.00009546652],"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":[0.00005010279,0.00002304103,0.0009078554,0.0001690961,0.00001520803,0.00003408896,0.00006920472,0.0001388619,0.9924225,0.0000706824,0.00006236802,0.006036926],"study_design_scores_gemma":[0.000008477193,0.000241691,0.006269326,0.00005685646,0.00007293075,0.0002444794,0.00005574262,0.001971671,0.9842449,0.0001680124,0.00663581,0.00003014985],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6252862,0.005492142,0.3576362,0.0009104364,0.0003070992,0.0007967764,0.002328167,0.002575333,0.004667702],"genre_scores_gemma":[0.4775822,0.003572779,0.5027239,0.000788739,0.00008210329,0.000986023,0.005505478,0.0008965923,0.007862199],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.002420193,"threshold_uncertainty_score":0.01279932,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.004335118355921335,"score_gpt":0.17365481333547,"score_spread":0.1693196949795486,"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."}}