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Record W2368578541

Feasibility of rapid treatment of BTEX in groundwater by Fenton’s reagent

2010· article· en· W2368578541 on OpenAlexaff
Chao Xu

Bibliographic record

VenueShuiwen dizhi gongcheng dizhi · 2010
Typearticle
Languageen
FieldEnvironmental Science
TopicWater Quality Monitoring and Analysis
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsBTEXReagentBenzeneChemistryTolueneOxidizing agentEnvironmental chemistryMolar ratioFenton's reagentGroundwaterInorganic chemistryXyleneNuclear chemistryOrganic chemistryHydrogen peroxideFenton reactionCatalysisGeology
DOInot available

Abstract

fetched live from OpenAlex

The removal effect of Fenton’s oxidation treatment of benzene,toluene,ethyl benzene,and xylenes(BTEX) in groundwater was investigated.The results show that Fenton’s reagent suggested a strong ability to oxidize BTEX.While H2O2 /BTEX(molar ratio) = 5 and 10,H2O2 /Fe(II)(molar ratio) = 4 and 8 were best for oxidizing BTEX.The removal rate was over 80%.While H2O2 /BTEX(molar ratio) = 20,Fenton’s reagent suggested an effectively oxidation and there was little impact of H2O2 /Fe(II) on Fenton’s treatment effect.The removal rate was 97% ~ 100% while H2O2 /Fe(II) = 10.The whole Fenton system displayed a strong oxide environment and pH reduced from 6 ~ 7 to around 3 immediately.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.174
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.026
GPT teacher head0.277
Teacher spread0.251 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations0
Published2010
Admission routes1
Has abstractyes

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