{"id":"W4223473080","doi":"10.1002/etc.5341","title":"Delineating Effluent Exposure and Cumulative Ecotoxicological Risk of Metals Downstream of a Saskatchewan Uranium Mill Using Autonomous Sensors","year":2022,"lang":"en","type":"article","venue":"Environmental Toxicology and Chemistry","topic":"Environmental Toxicology and Ecotoxicology","field":"Environmental Science","cited_by":8,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Saskatchewan","funders":"Global Water Futures","keywords":"Environmental science; Effluent; Mercury (programming language); Aquatic ecosystem; Sediment; Cadmium; Environmental chemistry; Water quality; Ecotoxicology; Hazard quotient; Risk assessment; Water pollution; Hydrology (agriculture); Ecology; Environmental engineering; Chemistry; Heavy metals; Geology; Biology","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":true,"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":[0.0002120956,0.0003005969,0.0002054785,0.000765903,0.0004723467,0.0008302389,0.0003630093,0.0003052989,0.0005109215],"category_scores_gemma":[0.0004725562,0.00021285,0.000203727,0.0009869759,0.0003502898,0.00021777,0.0006608174,0.0002554264,0.0001263151],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002488042,"about_ca_system_score_gemma":0.002099993,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.4506434,"about_ca_topic_score_gemma":0.7120857,"domain_scores_codex":[0.9997949,0.00002560486,0.00001217668,0.00005714124,0.00007359773,0.00003649897],"domain_scores_gemma":[0.9996303,0.00007144961,0.00008197443,0.00001695888,0.0001638827,0.00003535768],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001420302,0.00006411091,0.9351456,0.00003849739,0.00005795661,0.000312647,0.000470276,0.002745088,0.04643683,0.00008128838,0.0001205089,0.01438522],"study_design_scores_gemma":[0.000008008577,0.0002165358,0.9715944,0.00001395726,0.00005413711,0.0001193969,0.001502562,0.01181752,0.01401483,0.00009916373,0.0005391111,0.00002027236],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.998948,0.00002033577,0.000446987,0.00001188358,4.487662e-7,0.00001326135,0.00008446777,0.00000956277,0.0004649851],"genre_scores_gemma":[0.9972925,0.00007614435,0.001488632,0.00003058274,5.842177e-7,0.00001915135,0.0002379315,0.00000366646,0.0008507086],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5493566,"threshold_uncertainty_score":0.8960407,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008224198684112385,"score_gpt":0.2144490001883527,"score_spread":0.2062248015042403,"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."}}