{"id":"W3175518271","doi":"10.1002/edn3.224","title":"Proper environmental DNA metabarcoding data transformation reveals temporal stability of fish communities in a dendritic river system","year":2021,"lang":"en","type":"article","venue":"Environmental DNA","topic":"Environmental DNA in Biodiversity Studies","field":"Environmental Science","cited_by":68,"is_retracted":false,"has_abstract":true,"ca_institutions":"Institut National de la Recherche Scientifique; Université Laval","funders":"Canada Research Chairs","keywords":"Environmental DNA; Biodiversity; Abundance (ecology); Ecology; Tributary; Habitat; Relative species abundance; Sampling (signal processing); Biology; Geography; Cartography","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":["metaepi_narrow","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0007525107,0.0004407247,0.0005887919,0.00007239218,0.0003476602,0.00003357689,0.0009086005,0.0001522244,0.004409761],"category_scores_gemma":[0.00001954563,0.0004645695,0.0001511971,0.0001787915,0.001568962,0.001305929,0.002174159,0.0003513492,0.0004464487],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001422475,"about_ca_system_score_gemma":0.000007086863,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0005767901,"about_ca_topic_score_gemma":0.0005576973,"domain_scores_codex":[0.9963267,0.000540038,0.000858806,0.0007478253,0.0009361235,0.0005904721],"domain_scores_gemma":[0.9981195,0.0001257395,0.0002336087,0.001360729,0.000001515503,0.0001588561],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00004383246,0.0007428089,0.8899031,0.000125432,0.00006920861,0.00005429225,0.005467183,0.00006220348,0.1020592,0.00001411538,0.0002789109,0.001179664],"study_design_scores_gemma":[0.001385988,0.0001053593,0.8989091,0.0001301075,0.0001294844,0.00005739317,0.03604512,0.0005429352,0.05890551,0.00002747145,0.003130106,0.0006314533],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9946707,0.0002334902,0.00005879061,0.0001247177,0.0001253555,0.0006979726,0.002095392,0.00004442,0.001949179],"genre_scores_gemma":[0.9957123,0.0003366942,0.002097738,0.0001792127,0.00001962487,0.00003651496,0.001423884,0.00003584572,0.0001582044],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.04315371,"threshold_uncertainty_score":0.9997806,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03968858173605139,"score_gpt":0.2175332388751342,"score_spread":0.1778446571390828,"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."}}