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Record W2151847931 · doi:10.5539/mas.v3n8p15

Decolorization and COD Removal of Reactive Yellow 16 by Fenton Oxidation and Comparison of Dye Removal with Photo Fenton and Sono Fenton Process

2009· article· en· W2151847931 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

venuePublished in a venue whose home country is Canada.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueModern Applied Science · 2009
Typearticle
Languageen
FieldEnvironmental Science
TopicWater Quality Monitoring and Analysis
Canadian institutionsnot available
Fundersnot available
KeywordsChemistryPulp and paper industryOxidation processAdvanced oxidation processPollutantFenton reactionEnvironmental chemistryWastewaterOrganic matterChemical oxygen demandDegradation (telecommunications)BiodegradationHydrogen peroxideEnvironmental scienceCatalysisOrganic chemistryEnvironmental engineering

Abstract

fetched live from OpenAlex

Wastewaters from textile industry contain various pollutants including a high content of organic matter, surfactants, additives and dyes. Dyes have obtained notoriety as hazardous substances, because most of them are toxic and considered to be resistant to biodegradation. Recently, advanced oxidation processes (AOP) have received considerable attention because it is possible to degrade organic compounds and color from wastewaters. This study was performed to investigate the removal of COD and color for Reactive yellow 16 using Fenton oxidation. The comparisons of removal efficiencies were made among Fenton, Photo Fenton and Sono Fenton process. Removal of COD and color of 80% & 90%, 90% & 98%, and 82% & 95% can be achieved by Fenton, Photo Fenton and Sono Fenton process. The results showed that H2O2/Fe2+/UV process was more effective in COD and color removal.

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.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.046
Threshold uncertainty score0.475

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 studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.011
GPT teacher head0.263
Teacher spread0.252 · 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