{"id":"W4225422791","doi":"10.1016/j.scitotenv.2022.155323","title":"Electro-Fenton treatment of contaminated mine water to decrease thiosalts toxicity to Daphnia magna","year":2022,"lang":"en","type":"article","venue":"The Science of The Total Environment","topic":"Advanced oxidation water treatment","field":"Environmental Science","cited_by":5,"is_retracted":false,"has_abstract":false,"ca_institutions":"Université du Québec en Abitibi-Témiscamingue","funders":"Natural Sciences and Engineering Research Council of Canada; Canada Excellence Research Chairs, Government of Canada","keywords":"Daphnia magna; Toxicity; Effluent; Acute toxicity; Toxicology; Contamination; Environmental science; Environmental chemistry; Environmental protection; Biology; Chemistry; Environmental engineering; Ecology","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":[0.00007240422,0.0002440992,0.0001403569,0.0001091381,0.00009402648,0.0001205496,0.0001467778,0.0002323738,0.0008330644],"category_scores_gemma":[0.00006715465,0.00009285966,0.000190737,0.00007339987,0.00009699666,0.00009402425,0.0001092763,0.0001893274,0.00008936322],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001872728,"about_ca_system_score_gemma":0.0001635509,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002423448,"about_ca_topic_score_gemma":0.004988337,"domain_scores_codex":[0.9999498,0.000006925666,0.000004889442,0.00001122489,0.00001343218,0.00001373251],"domain_scores_gemma":[0.9999698,0.000004956064,0.000006725048,0.00000273245,0.00001023599,0.000005575813],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0001101249,0.0000181053,0.0001570787,0.00003214103,0.000005506374,0.0000239813,0.00001296834,0.00005446281,0.9978383,0.00002410792,0.00003330324,0.001689887],"study_design_scores_gemma":[0.00001489138,0.0004935003,0.004635348,0.000003971471,0.00002070782,0.00006802945,0.00002370098,0.0006076346,0.9930841,0.00002307922,0.001021704,0.000003378686],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9976786,0.0003689141,0.0009330072,0.00006908772,0.00002357782,0.00001140798,0.00007504538,0.00002261148,0.0008177635],"genre_scores_gemma":[0.9955285,0.00027044,0.001024161,0.00004514411,0.000003094171,0.000006414188,0.0001031141,0.00000350566,0.003015572],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.002423448,"threshold_uncertainty_score":0.004818738,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007197595591335684,"score_gpt":0.2115448813104745,"score_spread":0.2043472857191388,"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."}}