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Record W2407272075 · doi:10.2175/106143007x221085

Denitrification with Carbon Addition—Kinetic Considerations

2008· article· en· W2407272075 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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueWater Environment Research · 2008
Typearticle
Languageen
FieldEnvironmental Science
TopicWastewater Treatment and Nitrogen Removal
Canadian institutionsEnviroSim (Canada)
Fundersnot available
KeywordsHeterotrophMethanolEffluentChemistryPulp and paper industryWastewaterDenitrificationCarbon fibersNitrogenSewage treatmentEnvironmental engineeringSugarEnvironmental chemistryEnvironmental scienceOrganic chemistryBiologyMaterials scienceBacteria

Abstract

fetched live from OpenAlex

The Blue Plains Advanced Wastewater Treatment Plant (Washington, D.C.) uses methanol as an external carbon source in a postdenitrification process, to achieve low effluent total nitrogen concentrations. This becomes more difficult in winter, at lower mixed liquor temperatures and higher flows, as a consequence of the kinetic behavior of the methanol-utilizing heterotrophs. The paper reports on an experimental batch test study conducted on Blue Plains postdenitrification sludge to investigate (1) the maximum specific growth rate of methanol-utilizing heterotrophs (Mu(METH)); (2) the temperature dependency of the growth rate; and (3) the efficacy of alternate substrates (ethanol, acetate, and sugar). A limited number of tests were conducted on sludge from two other treatment plants with methanol addition.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
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 score0.059
Threshold uncertainty score0.997

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0100.004

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 head0.051
GPT teacher head0.254
Teacher spread0.203 · 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