{"id":"W2916796547","doi":"10.1111/1755-0998.13008","title":"Metabarcoding a diverse arthropod mock community","year":2019,"lang":"en","type":"article","venue":"Molecular Ecology Resources","topic":"Environmental DNA in Biodiversity Studies","field":"Environmental Science","cited_by":192,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Guelph","funders":"Ontario Ministry of Research, Innovation and Science","keywords":"Biology; Species evenness; Ion semiconductor sequencing; Environmental DNA; Amplicon; Abundance (ecology); Biodiversity; Evolutionary biology; DNA barcoding; Ecology; Species richness; Zoology; DNA sequencing; Polymerase chain reaction; Genetics; DNA; 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":[0.001326172,0.0007432357,0.0007015293,0.001834288,0.001044873,0.001202922,0.0006117022,0.0007538523,0.001701344],"category_scores_gemma":[0.002309754,0.0003678928,0.0006592297,0.001809271,0.000499437,0.0007308856,0.00127682,0.0006512589,0.001229273],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003612662,"about_ca_system_score_gemma":0.0005573712,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001299803,"about_ca_topic_score_gemma":0.00326931,"domain_scores_codex":[0.9982067,0.0002409842,0.0001295777,0.0008037121,0.0004916288,0.0001273726],"domain_scores_gemma":[0.9984277,0.0002409794,0.0002814925,0.0001615389,0.0007226332,0.0001656978],"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":[0.0002690922,0.00007420146,0.0131049,0.0003018317,0.00007452329,0.0001482767,0.0005294196,0.0005081783,0.9696711,0.0003619039,0.000334196,0.01462245],"study_design_scores_gemma":[0.0001384742,0.002126401,0.3222014,0.0002882778,0.0006577357,0.00192455,0.001547209,0.02196459,0.5741786,0.002725981,0.07205009,0.0001966076],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9139627,0.0008856456,0.07038067,0.0001914222,0.00006934055,0.0005907075,0.009642938,0.000646316,0.003630472],"genre_scores_gemma":[0.564926,0.0007771936,0.3880443,0.0006126887,0.00006313345,0.00113772,0.03875116,0.0006160293,0.005071778],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001834288,"threshold_uncertainty_score":0.007013559,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01022539471548772,"score_gpt":0.2047295715323287,"score_spread":0.194504176816841,"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."}}