{"id":"W4293762574","doi":"10.1016/j.chemosphere.2022.136236","title":"Levels of pesticides and trace metals in water, sediment, and fish of a large, agriculturally-dominated river","year":2022,"lang":"en","type":"article","venue":"Chemosphere","topic":"Environmental Toxicology and Ecotoxicology","field":"Environmental Science","cited_by":22,"is_retracted":false,"has_abstract":false,"ca_institutions":"Global Institute for Water Security; University of Saskatchewan","funders":"Global Water Futures; Western Economic Diversification Canada; Natural Sciences and Engineering Research Council of Canada; Canada Foundation for Innovation; Canada First Research Excellence Fund; University of Saskatchewan","keywords":"Environmental science; Pesticide; Sediment; Environmental chemistry; Drainage basin; Contamination; Water quality; Hydrology (agriculture); Mercury (programming language); Lindane; Trace metal; Water pollution; Surface water; Ecology; Environmental engineering; Chemistry; Geology; Biology; Geography","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001532114,0.0002010981,0.000219833,0.0004978535,0.0008079227,0.0005702833,0.0003023861,0.000440591,0.0005859567],"category_scores_gemma":[0.00028828,0.0002797769,0.0001887696,0.0004489597,0.0006808303,0.0003813253,0.0004642579,0.000236499,0.0001685558],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007487497,"about_ca_system_score_gemma":0.000537891,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.03637007,"about_ca_topic_score_gemma":0.0515882,"domain_scores_codex":[0.9998626,0.00002059322,0.00001242671,0.00005167921,0.00002692582,0.00002583937],"domain_scores_gemma":[0.9998049,0.0000431436,0.00004424455,0.00001063489,0.00004859915,0.00004848684],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.001104138,0.0003256531,0.8028436,0.00004148902,0.0001333828,0.0005982244,0.002098634,0.001033335,0.1872631,0.0001233006,0.0001467524,0.00428847],"study_design_scores_gemma":[0.00002069989,0.0003396283,0.9905703,0.000002268815,0.00003491477,0.0001928266,0.001707882,0.0013457,0.005461357,0.00005433231,0.0002592952,0.00001081188],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9998253,0.000005498781,0.00002397501,0.000004593019,2.024653e-7,0.000001066799,0.00003876012,0.000001174649,0.00009946799],"genre_scores_gemma":[0.9993829,0.00001348283,0.00007966519,0.000007302424,6.744083e-7,0.000003753721,0.00008445699,0.00000132256,0.0004264077],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.03637007,"threshold_uncertainty_score":0.07231677,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009034109970897892,"score_gpt":0.2183731940301131,"score_spread":0.2093390840592152,"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."}}