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Record W1978450103 · doi:10.1002/jctb.547

Photocatalytic pretreatment of contaminated groundwater for biological nitrification enhancement

2002· article· en· W1978450103 on OpenAlexaff
Zisheng Zhang, William A. Anderson, Murray Moo‐Young

Bibliographic record

VenueJournal of Chemical Technology & Biotechnology · 2002
Typearticle
Languageen
FieldEnergy
TopicAdvanced Photocatalysis Techniques
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsNitrificationPhotocatalysisEnvironmental chemistryAdsorptionChemistryGroundwaterWater treatmentContaminationNitritePulp and paper industryEnvironmental engineeringEnvironmental scienceNitrateNitrogenEcologyOrganic chemistryCatalysisBiology

Abstract

fetched live from OpenAlex

Abstract The sequential photocatalytic/biological treatment of a contaminated groundwater from a local industrial site was studied. The ground water contained approximately 100 mg dm −3 ammonia, as well as mg dm −3 levels of nitrification‐inhibiting organics such as chlorobenzene. An existing treatment system uses carbon adsorption pretreatment to remove the nitrification inhibitors before the water is treated in a biological nitrification system. Photocatalysis, using a corrugated plate photoreactor, was studied as an alternative to the carbon adsorption system for inhibitor removal. Photocatalytic pretreatment was found to significantly enhance the extent of biological nitrification. An optimal pretreatment time appeared to exist, since further pretreatment resulted in accumulation of nitrite. Although further study is required, there appears to be a potential for using photocatalysis to remove inhibitors from biological nitrification systems. © 2002 Society of Chemical Industry

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)0.000
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Research integrity
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 score0.044
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0020.001
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 head0.023
GPT teacher head0.268
Teacher spread0.245 · 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 designBench or experimental
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

Citations9
Published2002
Admission routes1
Has abstractyes

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