{"id":"W2802168330","doi":"10.1016/j.jglr.2018.04.010","title":"A fate and transport model for Asian carp environmental DNA in the Chicago area waterways system","year":2018,"lang":"en","type":"article","venue":"Journal of Great Lakes Research","topic":"Environmental DNA in Biodiversity Studies","field":"Environmental Science","cited_by":12,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"U.S. Army Corps of Engineers; U.S. Environmental Protection Agency","keywords":"Environmental DNA; Endangered species; Invasive species; Environmental science; Carp; Ecology; Fishery; Biology; Fish <Actinopterygii>; Biodiversity; Habitat","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0009805355,0.0007757021,0.001080571,0.001153165,0.00163135,0.002441554,0.002970544,0.003359799,0.01001847],"category_scores_gemma":[0.00204307,0.001016439,0.001620676,0.001131879,0.001550459,0.002609119,0.001537341,0.001605667,0.0007439957],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.005100878,"about_ca_system_score_gemma":0.003488187,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.3016537,"about_ca_topic_score_gemma":0.1706274,"domain_scores_codex":[0.9997038,0.00009148286,0.0000126647,0.00006776148,0.0000193355,0.0001049106],"domain_scores_gemma":[0.9989141,0.0005275254,0.0001296553,0.00004666499,0.0002104615,0.0001716386],"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":[0.00006026501,0.00004658576,0.003768924,0.00001852658,0.00002641243,0.0001513784,0.00009847197,0.9799888,0.0003565464,0.01331813,0.001183544,0.0009824561],"study_design_scores_gemma":[0.00002545748,0.00001623741,0.0008050849,0.00000645787,0.00002280442,0.00002009407,0.0001497865,0.994495,0.00007288303,0.004016548,0.0003502575,0.00001937979],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9213365,0.0002848352,0.04167546,0.004105127,0.00009897212,0.000127231,0.002987786,0.0003260651,0.02905804],"genre_scores_gemma":[0.9661964,0.0001640282,0.002620995,0.0001678939,0.00003120346,0.00008802721,0.0006821741,0.0001115784,0.02993767],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3016537,"threshold_uncertainty_score":0.5997957,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05486827306507967,"score_gpt":0.2774457836271167,"score_spread":0.2225775105620371,"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."}}