{"id":"W3200689953","doi":"10.1016/j.jhazmat.2021.127295","title":"Removal of arsenic and metals from groundwater impacted by mine waste using zero-valent iron and organic carbon: Laboratory column experiments","year":2021,"lang":"en","type":"article","venue":"Journal of Hazardous Materials","topic":"Arsenic contamination and mitigation","field":"Environmental Science","cited_by":29,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Waterloo","funders":"Argonne National Laboratory; Natural Sciences and Engineering Research Council of Canada; Canadian Institutes of Health Research; Office of Science; University of Saskatchewan; Canadian Light Source; U.S. Department of Energy","keywords":"Zerovalent iron; Environmental chemistry; Acid mine drainage; Ferrihydrite; Environmental remediation; Arsenic; Chemistry; Sulfate; Groundwater; Realgar; Effluent; Activated carbon; Permeable reactive barrier; Total organic carbon; Ferrous; Schwertmannite; Adsorption; Contamination; Environmental science; Environmental engineering; Mineralogy; Geology; Goethite","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":[0.0003238653,0.0001208738,0.0003392972,0.00003124039,0.00004435259,0.00005741228,0.00006108166,0.00006465676,0.0009646507],"category_scores_gemma":[0.00004762099,0.0001069996,0.00003105377,0.00007435984,0.00009017599,0.0002245463,0.0001044857,0.00004901682,0.000002336828],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001175562,"about_ca_system_score_gemma":0.0000374276,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001512165,"about_ca_topic_score_gemma":0.0000231419,"domain_scores_codex":[0.9987438,0.0001754876,0.0005193549,0.0001529826,0.0002773411,0.0001310346],"domain_scores_gemma":[0.9992463,0.00002736249,0.00046463,0.000112976,0.00005045465,0.00009826196],"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":[0.00004521422,0.00005666654,0.0006637115,0.00001146664,0.00004289127,0.00008688115,0.0005444003,0.000003418577,0.9980403,0.000001094448,0.0002140306,0.0002898771],"study_design_scores_gemma":[0.0009636887,0.0000999279,0.004311511,0.00005078938,0.0001026223,0.0003475397,0.0004174745,0.00005167822,0.9931011,0.00004608736,0.0003947153,0.000112935],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9982966,0.001095663,0.00004956771,0.00008528902,0.0002912079,0.00008432207,0.00004066584,0.000004224943,0.00005243716],"genre_scores_gemma":[0.9983581,0.0001611246,0.001114633,0.00006618456,0.00005082539,6.981561e-7,0.000009124777,0.00001462278,0.0002246578],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.004939317,"threshold_uncertainty_score":0.9999486,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009498026625027946,"score_gpt":0.2291947942755403,"score_spread":0.2196967676505124,"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."}}