{"id":"W4405497520","doi":"10.1002/edn3.70015","title":"Evaluating Sampling Designs to Survey Fish Diversity in Lakes From Northern Temperate Zones","year":2024,"lang":"en","type":"article","venue":"Environmental DNA","topic":"Environmental DNA in Biodiversity Studies","field":"Environmental Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Ministère de l’Environnement, de la Lutte contre les changements climatiques, de la Faune et des Parcs; Ministère des Ressources naturelles et des Forêts; Université Laval","funders":"Natural Sciences and Engineering Research Council of Canada; Génome Québec","keywords":"Temperate climate; Fish <Actinopterygii>; Sampling (signal processing); Diversity (politics); Fishery; Geography; Ecology; Sampling design; Environmental science; Biology; Engineering; 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.01508041,0.0005372344,0.000357576,0.0009896664,0.0008728353,0.0005146416,0.0007352508,0.0004612966,0.0005283456],"category_scores_gemma":[0.01442594,0.0002915846,0.0004113333,0.0007529929,0.0007311222,0.0003977722,0.0006671975,0.0001927021,0.0001061199],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003558146,"about_ca_system_score_gemma":0.002896386,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.09141716,"about_ca_topic_score_gemma":0.2430351,"domain_scores_codex":[0.9931597,0.00473542,0.0003709798,0.0005335597,0.000872778,0.0003275787],"domain_scores_gemma":[0.9876001,0.00547277,0.002416781,0.0005906051,0.003491429,0.0004283005],"domain_codex":null,"domain_gemma":"methods","domain_candidate":"methods","domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.003941461,0.0009076229,0.7598133,0.0007657867,0.0005209445,0.0001758035,0.002500521,0.02715578,0.1072129,0.0007631403,0.0007180996,0.09552463],"study_design_scores_gemma":[0.0003517213,0.007339144,0.9233776,0.0001310035,0.0002308711,0.00009712962,0.001456164,0.03400502,0.02954225,0.0004165429,0.002966071,0.00008641301],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9779157,0.0002704895,0.01983298,0.00004687662,0.000007872537,0.001210689,0.00018322,0.0000571731,0.0004749701],"genre_scores_gemma":[0.9219862,0.0001817096,0.07505812,0.00009279314,0.000006971382,0.001859825,0.0003850885,0.00001044934,0.0004189726],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9849196,"threshold_uncertainty_score":0.1817701,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1031422426852203,"score_gpt":0.2872249845323366,"score_spread":0.1840827418471163,"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."}}