{"id":"W2033667350","doi":"10.1016/j.watres.2015.04.009","title":"Enhanced reductive dechlorination of trichloroethylene by sulfidated nanoscale zerovalent iron","year":2015,"lang":"en","type":"article","venue":"Water Research","topic":"Environmental remediation with nanomaterials","field":"Engineering","cited_by":394,"is_retracted":false,"has_abstract":false,"ca_institutions":"McGill University","funders":"Fonds de recherche du Québec – Nature et technologies; Natural Sciences and Engineering Research Council of Canada","keywords":"Sulfidation; Zerovalent iron; Trichloroethylene; Chemistry; Reaction rate constant; Sulfide; Iron sulfide; Environmental remediation; Reductive dechlorination; Inorganic chemistry; X-ray photoelectron spectroscopy; Nuclear chemistry; Environmental chemistry; Adsorption; Chemical engineering; Kinetics; Contamination; Biodegradation; Organic chemistry; Sulfur","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":[0.0001272604,0.0002437039,0.0001547525,0.0001205697,0.0001062072,0.0001804661,0.0001839543,0.0002009653,0.0007823212],"category_scores_gemma":[0.0001432039,0.00009116436,0.0001494228,0.00007834079,0.000141331,0.0001694418,0.0001633966,0.0002191734,0.0001943387],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003583184,"about_ca_system_score_gemma":0.0002918399,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002999721,"about_ca_topic_score_gemma":0.006998024,"domain_scores_codex":[0.9999319,0.000007034187,0.000003699093,0.00001247274,0.00002050573,0.00002439735],"domain_scores_gemma":[0.9999616,0.000006175357,0.000005954054,0.000004567235,0.00001614136,0.000005553065],"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":[0.00006556812,0.00001359669,0.0001485463,0.00002631869,0.00000385302,0.00003434671,0.00003527982,0.0001315581,0.9971495,0.0001018402,0.00005263575,0.002236941],"study_design_scores_gemma":[0.000003219475,0.0000442216,0.0003410025,0.000001044973,0.000002851203,0.00001891642,0.00001076701,0.0005676837,0.998528,0.00001272677,0.000468237,0.000001333647],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9970426,0.0001703709,0.001359107,0.00004843531,0.00001044843,0.00000760204,0.00004525029,0.00002545475,0.001290704],"genre_scores_gemma":[0.9956461,0.0001532226,0.0008135941,0.00001633157,0.000002239276,0.000002585296,0.00008058434,0.000007673117,0.003277675],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.002999721,"threshold_uncertainty_score":0.005964518,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04028459770525743,"score_gpt":0.2986065977156317,"score_spread":0.2583220000103743,"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."}}