{"id":"W4377010801","doi":"10.1186/s12862-023-02118-w","title":"Hidden diversity: DNA metabarcoding reveals hyper-diverse benthic invertebrate communities","year":2023,"lang":"en","type":"article","venue":"BMC Ecology and Evolution","topic":"Environmental DNA in Biodiversity Studies","field":"Environmental Science","cited_by":15,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Guelph; Agriculture and Agri-Food Canada","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Biomonitoring; Benthic zone; Ecology; Biodiversity; Invertebrate; Aquatic insect; Environmental DNA; Taxonomic rank; STREAMS; Beta diversity; Biology; Freshwater ecosystem; Taxon; Aquatic ecosystem; Spatial ecology; Species richness; Community structure; Community; Ecosystem; Metacommunity; Habitat; Biological dispersal; Population","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":"codex-gemma-dda1882f352a","candidate_categories":["sts","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0003604146,0.0001281546,0.0001619537,0.00007638367,0.001589224,0.00001145767,0.0001981917,0.0001105877,0.0006572418],"category_scores_gemma":[0.00003455265,0.0001351909,0.00004629039,0.0001910485,0.0006887898,0.0003014827,0.002571292,0.0001342254,0.002636915],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002557627,"about_ca_system_score_gemma":0.000002371544,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0007462669,"about_ca_topic_score_gemma":0.002302383,"domain_scores_codex":[0.999042,0.000172558,0.0001148665,0.0002143755,0.000158095,0.0002981121],"domain_scores_gemma":[0.9995885,0.000124953,0.00006059351,0.000155414,0.000003779513,0.00006668946],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00001250247,0.00002272956,0.9912595,0.00001113984,0.00002196544,0.000004109483,0.001310194,0.00006913995,0.000662159,0.0001727153,0.006331973,0.0001218934],"study_design_scores_gemma":[0.0003102378,0.0000569324,0.9904478,0.000005817661,0.00005739268,0.000004977983,0.006689267,0.0005481621,0.00005077155,0.001324832,0.0003553875,0.0001484532],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9975297,0.0000589284,0.00001777365,0.0002211157,0.0002110907,0.0001556286,0.00002369405,0.0001052872,0.001676715],"genre_scores_gemma":[0.9975064,0.000308235,0.0005518649,0.0002137184,0.00001728664,0.000008031429,0.00002506788,0.00000511522,0.001364281],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.005976585,"threshold_uncertainty_score":0.9997106,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04536158092803295,"score_gpt":0.2252043060679842,"score_spread":0.1798427251399512,"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."}}