{"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":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.000512085,0.0002199814,0.0002166113,0.00006440899,0.0005373934,0.00001287173,0.0009633966,0.00001598723,0.003406329],"category_scores_gemma":[0.00003196817,0.0001137018,0.0001027893,0.0004591815,0.0006361016,0.0001298868,0.001483566,0.00006729655,0.0002153772],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001641175,"about_ca_system_score_gemma":0.00002989157,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0005121555,"about_ca_topic_score_gemma":0.000009218457,"domain_scores_codex":[0.997354,0.0001358268,0.0003379374,0.0004982125,0.001161169,0.0005128995],"domain_scores_gemma":[0.9985776,0.00003358396,0.0001306028,0.0009570373,0.000006132982,0.0002950761],"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":[0.0001021775,0.0004924956,0.0001928426,0.000001161875,0.00001072122,0.000001706959,0.002041118,0.2223404,0.7728247,0.0000256047,0.00006134653,0.001905727],"study_design_scores_gemma":[0.000463851,0.001366083,0.02577867,0.000004089731,0.00003771215,0.00001487447,0.0002319459,0.0005743008,0.9697842,0.0001768127,0.00141027,0.0001571811],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9947641,0.00001460757,0.00008674037,0.003194598,0.0001098835,0.001226065,0.00003673057,0.00001364117,0.0005535825],"genre_scores_gemma":[0.9946642,0.000006154667,0.0009487194,0.0001572888,0.000008699098,0.0001969711,0.000004685484,0.00001402293,0.00399929],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2217661,"threshold_uncertainty_score":0.9975047,"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."}}