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Bioaugmentation with Nitrifying Bacteria Acclimated to Different Temperatures

2005· article· en· W2160217942 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

VenueJournal of Environmental Engineering · 2005
Typearticle
Languageen
FieldEnvironmental Science
TopicWastewater Treatment and Nitrogen Removal
Canadian institutionsUniversity of Manitoba
Fundersnot available
KeywordsNitrificationNitrifying bacteriaBioaugmentationHydraulic retention timeSeedingChemistrySequencing batch reactorPulp and paper industryBiomass (ecology)Environmental engineeringEnvironmental chemistryEnvironmental scienceWastewaterBacteriaBiologyAgronomyNitrogenMicroorganism

Abstract

fetched live from OpenAlex

A nitrifying biomass was produced from anaerobic sludge dewatering liquors for the purpose of bioaugmentation of sequencing batch reactors (SBRs). Nitrification of centrate was conducted at four temperatures (10, 20, 25, and 30°C) while the seeded SBRs were operated at 10°C with a solids retention time of approximately 4 days. The SBRs did not exhibit any nitrification before the onset of seeding. When the hydraulic retention time (HRT) was 24 h, partial removal of NH3–N occurred when seed acclimated to 20, 25, and 30°C was added. When the HRT was 12 h, only the SBR seeded with nitrifying biomass acclimated to 10°C achieved 50% NH3–N removal. Complete removal of NH3–N was not achieved in any of the seeded SBRs. The degree of NH3–N removal in the seeded SBRs was dependent on the initial temperature of the seed, and the observed growth rates of the nitrifying bacteria were inversely proportional to the change in temperature.

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 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 score0.217
Threshold uncertainty score0.963

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 studies0.0000.000
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 head0.005
GPT teacher head0.181
Teacher spread0.177 · 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