{"id":"W2081133538","doi":"10.1029/2001wr000234","title":"Reactive transport modeling of an in situ reactive barrier for the treatment of hexavalent chromium and trichloroethylene in groundwater","year":2001,"lang":"en","type":"article","venue":"Water Resources Research","topic":"Environmental remediation with nanomaterials","field":"Engineering","cited_by":160,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo; University of British Columbia","funders":"Natural Sciences and Engineering Research Council of Canada; Government of Canada; Pacific Northwest National Laboratory; U.S. Environmental Protection Agency","keywords":"Permeable reactive barrier; Hexavalent chromium; Environmental remediation; Groundwater; Aquifer; Zerovalent iron; Sulfate; Chemistry; Environmental chemistry; Chromium; Contamination; Geology; Adsorption; Geotechnical engineering","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":[0.0003611536,0.0008032473,0.0008848242,0.0005202727,0.001043685,0.001191001,0.00149781,0.002025937,0.00268309],"category_scores_gemma":[0.0006577953,0.0005556319,0.001076398,0.0006435375,0.0006055312,0.0007116853,0.0005421069,0.0008147963,0.0002128981],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003433058,"about_ca_system_score_gemma":0.002756323,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.1261873,"about_ca_topic_score_gemma":0.04974413,"domain_scores_codex":[0.9998618,0.00002971763,0.000005360401,0.00002906496,0.00002662426,0.0000473997],"domain_scores_gemma":[0.9996278,0.0001832533,0.00003850671,0.00001431766,0.00009441782,0.00004173431],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00004373953,0.00004925202,0.0009054544,0.00002074301,0.00001042298,0.00007542968,0.00002639191,0.9951233,0.0025383,0.0006991038,0.00008809041,0.0004197291],"study_design_scores_gemma":[0.00001894564,0.00003185106,0.0002077939,0.000001934509,0.000005665557,0.000006464132,0.00003301126,0.9988191,0.000621376,0.0001092674,0.0001389911,0.000005643501],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9757069,0.0001100712,0.01232041,0.0003576982,0.00003242589,0.00009570338,0.0007550748,0.0001043465,0.0105173],"genre_scores_gemma":[0.9901568,0.0001718527,0.005033453,0.000070554,0.00000699995,0.0001455164,0.0003771143,0.00004583066,0.003992008],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1261873,"threshold_uncertainty_score":0.2509056,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04042988703043895,"score_gpt":0.2917944060631769,"score_spread":0.2513645190327379,"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."}}