{"id":"W2740453096","doi":"10.1007/s12686-017-0817-y","title":"Establishing detection thresholds for environmental DNA using receiver operator characteristic (ROC) curves","year":2017,"lang":"en","type":"article","venue":"Conservation Genetics Resources","topic":"Environmental DNA in Biodiversity Studies","field":"Environmental Science","cited_by":29,"is_retracted":false,"has_abstract":false,"ca_institutions":"Trent University; Ministry of Natural Resources and Forestry","funders":"Ontario Ministry of Natural Resources and Forestry","keywords":"Receiver operating characteristic; Environmental DNA; Sensitivity (control systems); Biology; Fish <Actinopterygii>; Endangered species; Statistics; Biodiversity; Data mining; Computer science; Ecology; Mathematics; Engineering; Fishery","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false,"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":[0.0002312076,0.0002059159,0.0001765015,0.00003091177,0.001765626,0.0002268021,0.0004931228,0.00009623769,0.0003570227],"category_scores_gemma":[0.00015355,0.0002207411,0.00007088152,0.00003918408,0.0005782215,0.0004578247,0.0005353838,0.00009361938,0.00009250531],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002638627,"about_ca_system_score_gemma":0.000003237293,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001146686,"about_ca_topic_score_gemma":0.00008366755,"domain_scores_codex":[0.9986656,0.00004312927,0.0002400838,0.0004388479,0.0003329875,0.0002793641],"domain_scores_gemma":[0.9990554,0.00007462857,0.0002898051,0.000481896,0.000007491079,0.00009078602],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00002510558,0.00003732374,0.834224,0.0000273659,0.00002139815,0.00000159353,0.0003107614,0.0001498448,0.1607251,5.282337e-7,0.0007455361,0.003731432],"study_design_scores_gemma":[0.00038117,0.00007045194,0.9373144,0.00004900616,0.00006351482,0.000004721524,0.0002072874,0.003816748,0.0212341,0.00002143757,0.03654907,0.0002880787],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9973886,0.0003235653,0.0005734703,0.0003563059,0.000239469,0.0005170474,0.0001159414,0.00003091058,0.0004546998],"genre_scores_gemma":[0.9942833,0.0006720694,0.003435075,0.0006954386,0.0000958723,0.00003309203,0.00003281493,0.0000248363,0.0007275554],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.139491,"threshold_uncertainty_score":0.999534,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03806468695687287,"score_gpt":0.2500363382520598,"score_spread":0.211971651295187,"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."}}