{"id":"W2768861940","doi":"10.1002/cjce.23073","title":"Degradation of ferrate species produced electrochemically for use in drinking water treatment applications","year":2017,"lang":"en","type":"article","venue":"The Canadian Journal of Chemical Engineering","topic":"Advanced oxidation water treatment","field":"Environmental Science","cited_by":15,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"Natural Sciences and Engineering Research Council of Canada; Universities Space Research Association","keywords":"Degradation (telecommunications); Water treatment; Chemistry; Arrhenius equation; Impurity; Reaction rate constant; Electrochemistry; Environmental chemistry; Tap water; Activation energy; Inorganic chemistry; Kinetics; Environmental engineering; Environmental science; Organic chemistry; Electrode","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":true,"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":[0.0003850497,0.000281172,0.0002755916,0.0002969234,0.00017823,0.0003315289,0.0002771615,0.000444596,0.0006021727],"category_scores_gemma":[0.0008069159,0.0001267854,0.000281464,0.0002279633,0.0002092178,0.0002856407,0.0001821796,0.0002887842,0.000162789],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005414854,"about_ca_system_score_gemma":0.0002357284,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001584184,"about_ca_topic_score_gemma":0.003062151,"domain_scores_codex":[0.9997825,0.00002988141,0.00001589537,0.00003621496,0.0001044967,0.00003106067],"domain_scores_gemma":[0.9998197,0.00003827014,0.00004253526,0.00001503072,0.00007408193,0.00001029687],"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":[0.00003602428,0.00001535616,0.0002677055,0.00007765937,0.000005466517,0.00002777125,0.00001997928,0.0001338706,0.9958366,0.0000390862,0.00003198345,0.00350853],"study_design_scores_gemma":[0.000002361675,0.00009419543,0.0007538701,0.000004189297,0.000004996758,0.00004985902,0.00001797691,0.000284175,0.9982078,0.00001779588,0.000560322,0.000002459545],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9876179,0.002116083,0.008159308,0.0001277497,0.0000311546,0.00004747353,0.0001624969,0.00006726968,0.001670574],"genre_scores_gemma":[0.9891423,0.001988478,0.006509191,0.00004492579,0.000007461564,0.000019582,0.0001624843,0.00002262588,0.002102972],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001584184,"threshold_uncertainty_score":0.003928721,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01939191587882834,"score_gpt":0.2163990249754905,"score_spread":0.1970071090966621,"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."}}