{"id":"W2519928782","doi":"10.1111/1755-0998.12598","title":"Residual <scp>eDNA</scp> detection sensitivity assessed by quantitative real‐time <scp>PCR</scp> in a river ecosystem","year":2016,"lang":"en","type":"article","venue":"Molecular Ecology Resources","topic":"Environmental DNA in Biodiversity Studies","field":"Environmental Science","cited_by":55,"is_retracted":false,"has_abstract":true,"ca_institutions":"Fisheries and Oceans Canada; University of Windsor","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Environmental DNA; River ecosystem; Biology; Residual; Aquatic ecosystem; Ecology; Sampling (signal processing); Real-time polymerase chain reaction; Ecosystem; Biodiversity","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":["metaepi_narrow","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0007687492,0.0003915843,0.0004834211,0.0001427532,0.0003538137,0.00003392018,0.0003249043,0.0003446146,0.00008222209],"category_scores_gemma":[0.0007108686,0.0003443924,0.0001222121,0.0003210313,0.0008928954,0.0002780458,0.0007280675,0.0002354157,0.002279126],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007706273,"about_ca_system_score_gemma":0.000006420167,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004973428,"about_ca_topic_score_gemma":0.002317204,"domain_scores_codex":[0.996389,0.001041341,0.0003700516,0.0009450257,0.0004731794,0.0007814458],"domain_scores_gemma":[0.997659,0.001494009,0.0002791953,0.0003933249,0.00001369129,0.0001607787],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","study_design_scores_codex":[0.00001025273,0.0001713444,0.4396384,0.00001029758,0.00009717761,0.0002048732,0.001396969,0.0001718771,0.5542061,0.000007572649,0.003838961,0.0002461267],"study_design_scores_gemma":[0.001037517,0.0006136866,0.8448541,0.00002838879,0.0000593152,0.00002774597,0.001213648,0.0001294102,0.13864,0.000111881,0.01315049,0.0001338822],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9947051,0.0000880425,0.0002500267,0.0001528707,0.0001022488,0.0005162609,0.0001715581,0.0001131815,0.003900757],"genre_scores_gemma":[0.9967327,0.00008443706,0.0009317241,0.0001977163,0.00001877621,0.00004703371,0.00001371812,0.0000352971,0.001938595],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4155662,"threshold_uncertainty_score":0.9999008,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.006333004548253655,"score_gpt":0.200191816780318,"score_spread":0.1938588122320644,"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."}}