{"id":"W2795884710","doi":"10.1016/j.envpol.2018.02.081","title":"eDNA-based bioassessment of coastal sediments impacted by an oil spill","year":2018,"lang":"en","type":"article","venue":"Environmental Pollution","topic":"Environmental DNA in Biodiversity Studies","field":"Environmental Science","cited_by":71,"is_retracted":false,"has_abstract":false,"ca_institutions":"Global Institute for Water Security; University of Saskatchewan","funders":"Major Science and Technology Program for Water Pollution Control and Treatment; University of Hong Kong; Global Water Futures; Ministry of Oceans and Fisheries; Fundamental Research Funds for the Central Universities; Nanjing University; State Administration of Foreign Experts Affairs; Chinese Academy of Sciences; Canada Research Chairs","keywords":"Biota; Ecology; Environmental science; Pollution; Ecosystem; Biology","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":["insufficient_payload"],"category_scores_codex":[0.0001948961,0.0003297993,0.0002430099,0.00005513369,0.0003501278,0.00001709485,0.0003338798,0.0001289426,0.005165811],"category_scores_gemma":[0.000007422946,0.0003344533,0.0001029208,0.0001538378,0.001839273,0.0003799954,0.0004142714,0.0001250871,0.00125128],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007511427,"about_ca_system_score_gemma":0.000004662574,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0005996297,"about_ca_topic_score_gemma":0.0000550749,"domain_scores_codex":[0.997709,0.0001077168,0.0003475336,0.0005789724,0.000772666,0.0004841351],"domain_scores_gemma":[0.9990826,0.00001496299,0.0002296082,0.0004373099,0.000001937821,0.0002335598],"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":[0.00009705975,0.0008417673,0.3893876,0.00000499309,0.00003681121,0.000002619523,0.0002265213,0.0001399839,0.5982446,0.000002796536,0.004646133,0.006369093],"study_design_scores_gemma":[0.00121465,0.001101432,0.7560699,0.00001308479,0.00005138449,0.000002973484,0.0004824516,0.0005264498,0.2344251,0.00002044906,0.005692781,0.0003993282],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9957121,0.00004131836,0.0002359922,0.0001732443,0.0002059837,0.0001851509,0.0008422654,0.00005752279,0.002546426],"genre_scores_gemma":[0.995922,0.00004721114,0.002629862,0.0004559798,0.00005629014,0.00001153711,0.0003103537,0.00002669888,0.0005400677],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3666823,"threshold_uncertainty_score":0.9999108,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008532140989964921,"score_gpt":0.2214056169389592,"score_spread":0.2128734759489943,"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."}}