{"id":"W3134156743","doi":"10.3897/aca.4.e65379","title":"Replicate DNA metabarcoding can discriminate seasonal and spatial abundance shifts in river macroinvertebrate assemblages","year":2021,"lang":"en","type":"article","venue":"ARPHA Conference Abstracts","topic":"Environmental DNA in Biodiversity Studies","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Guelph; University of New Brunswick","funders":"","keywords":"Abundance (ecology); Replicate; Benthic zone; Ecology; Biodiversity; Tributary; Environmental DNA; Biology; Relative species abundance; Geography; Environmental science; Cartography; Statistics","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"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":[0.002404736,0.0004041331,0.0003948303,0.001240366,0.0004259071,0.0007708902,0.0006550361,0.0005903131,0.0004944626],"category_scores_gemma":[0.008596215,0.0005449922,0.0004643943,0.0008317597,0.0005639091,0.0007549216,0.0005258198,0.0004624373,0.0004184619],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003741932,"about_ca_system_score_gemma":0.0003810441,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007463225,"about_ca_topic_score_gemma":0.0251409,"domain_scores_codex":[0.9982857,0.0004319012,0.0001227629,0.0007968429,0.0002938638,0.0000689109],"domain_scores_gemma":[0.9943666,0.002161152,0.001779258,0.0007830627,0.0007392397,0.000170713],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0004315237,0.0001487499,0.7034641,0.0003476193,0.0007226025,0.0001445963,0.001166523,0.004451615,0.2014296,0.000515016,0.0006386164,0.08653954],"study_design_scores_gemma":[0.0000241887,0.0003254705,0.9228035,0.0000385045,0.0002915602,0.0003826157,0.0003872426,0.03551747,0.03665894,0.0009829192,0.002486436,0.0001011194],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9205827,0.0005863127,0.07561946,0.00007818442,0.00003644008,0.0000982369,0.001197155,0.0003473265,0.001454234],"genre_scores_gemma":[0.9165661,0.0001562915,0.08098666,0.0001072012,0.00001865323,0.0001065618,0.001285607,0.00005126613,0.0007216379],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.007463225,"threshold_uncertainty_score":0.01483953,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02400295276737163,"score_gpt":0.2291791940438094,"score_spread":0.2051762412764377,"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."}}