{"id":"W3025890805","doi":"10.1002/edn3.88","title":"Caged fish experiment and hydrodynamic bidimensional modeling highlight the importance to consider 2D dispersion in fluvial environmental DNA studies","year":2020,"lang":"en","type":"article","venue":"Environmental DNA","topic":"Environmental DNA in Biodiversity Studies","field":"Environmental Science","cited_by":83,"is_retracted":false,"has_abstract":true,"ca_institutions":"GDG Environnement; Ministère des Ressources naturelles et des Forêts; Université Laval","funders":"Natural Sciences and Engineering Research Council of Canada; Ministère des Forêts, de la Faune et des Parcs","keywords":"Environmental DNA; Salmo; Environmental science; Brown trout; Dispersion (optics); Fluvial; River ecosystem; Rainbow trout; Abundance (ecology); Hydrology (agriculture); Fish <Actinopterygii>; Fishery; Ecology; Geology; Ecosystem; Biology; Biodiversity; Physics; Geomorphology; Structural basin","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000552276,0.0003944284,0.0004753443,0.0002220021,0.0002317372,0.0005321537,0.0005428492,0.0006058138,0.001379795],"category_scores_gemma":[0.001393845,0.0002298352,0.0004542651,0.0001823345,0.0003142504,0.0008869248,0.0003641106,0.0003744981,0.0001703027],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004762155,"about_ca_system_score_gemma":0.0005071604,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01378604,"about_ca_topic_score_gemma":0.01002715,"domain_scores_codex":[0.9998491,0.00005247366,0.00001284228,0.00005358874,0.00001733868,0.0000147124],"domain_scores_gemma":[0.9994466,0.0003189371,0.00007484286,0.00007329162,0.00005749906,0.00002877919],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.000069299,0.0001179893,0.02304249,0.00008676158,0.00007943594,0.0001227566,0.0000583663,0.9566849,0.01142602,0.001945614,0.0003706191,0.005995585],"study_design_scores_gemma":[0.00001063104,0.00007453625,0.007377516,0.000006559849,0.00001446167,0.00001537849,0.00002454346,0.9900343,0.001506682,0.0004745538,0.0004444699,0.00001633096],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8624694,0.0002073875,0.1327682,0.0002790092,0.0000655129,0.0001176737,0.0008318272,0.0002540494,0.003007037],"genre_scores_gemma":[0.9815439,0.0001021074,0.01642142,0.00005548531,0.000009547653,0.0001461843,0.0002794529,0.00004751213,0.001394423],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01378604,"threshold_uncertainty_score":0.02741158,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02173306456648412,"score_gpt":0.2256656313660058,"score_spread":0.2039325667995217,"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."}}