{"id":"W4210371880","doi":"10.1139/cjfas-2021-0215","title":"Fish community surveys in eelgrass beds using both eDNA metabarcoding and seining: implications for biodiversity monitoring in the coastal zone","year":2022,"lang":"en","type":"article","venue":"Canadian Journal of Fisheries and Aquatic Sciences","topic":"Environmental DNA in Biodiversity Studies","field":"Environmental Science","cited_by":25,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Guelph; University of British Columbia; Bedford Institute of Oceanography; Fisheries and Oceans Canada","funders":"Fisheries and Oceans Canada","keywords":"Biodiversity; Environmental DNA; Fishery; Species richness; Abundance (ecology); Ecology; Zostera marina; Ecosystem; Geography; Biology; Seagrass","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":true,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["sts"],"consensus_categories":[],"category_scores_codex":[0.003309762,0.00006905747,0.000121529,0.00009294142,0.002354023,0.00009638653,0.0003322711,0.00001364595,0.00002369461],"category_scores_gemma":[0.0001075303,0.00005915897,0.00002291098,0.0003185016,0.001269261,0.000306955,0.0001593188,0.0002088888,1.301731e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001317877,"about_ca_system_score_gemma":0.00002806442,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.04600538,"about_ca_topic_score_gemma":0.0573145,"domain_scores_codex":[0.9989769,0.0004119027,0.0001544788,0.0001007806,0.0001533454,0.0002025407],"domain_scores_gemma":[0.9994176,0.0003228326,0.0001026724,0.00006350839,0.000002656025,0.00009072012],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.000001400463,0.00001028506,0.9924761,0.000002242728,0.000003767865,0.000003375828,0.005861401,0.0001300321,0.0001069277,0.000005354344,0.0001104267,0.001288705],"study_design_scores_gemma":[0.0001748056,0.000114047,0.9504381,0.000007910517,0.00001077047,0.00002438574,0.04845208,0.0001571844,0.000012897,0.0001809261,0.0003588443,0.00006800822],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9976858,0.00009835695,0.0001637512,0.001746612,0.0000768979,0.0001028219,0.00005289139,8.823147e-7,0.00007202379],"genre_scores_gemma":[0.9982323,0.00003255473,0.001589105,0.0001287954,0.000006782579,0.000002458864,0.00000110487,0.000001317699,0.000005592806],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.04259067,"threshold_uncertainty_score":0.9989448,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07879899292546098,"score_gpt":0.2537318446876792,"score_spread":0.1749328517622182,"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."}}