MétaCan
Menu
Back to cohort
Record W2036133458 · doi:10.2166/wst.2009.419

Kinetic analysis of attached growth nitrification in cold climates

2009· article· en· W2036133458 on OpenAlexaff
Robert Delatolla, Nathalie Tufenkji, Yves Comeau, Alain Gadbois, Daniel Lamarre, Dimitrios Berk

Bibliographic record

VenueWater Science & Technology · 2009
Typearticle
Languageen
FieldEnvironmental Science
TopicWastewater Treatment and Nitrogen Removal
Canadian institutionsPolytechnique MontréalMcGill University
Fundersnot available
KeywordsNitrificationAmmoniaChemistryAerationAnimal scienceEnvironmental chemistryFiltration (mathematics)Environmental engineeringNitrogenEnvironmental scienceBiochemistryBiologyOrganic chemistry

Abstract

fetched live from OpenAlex

The rate of nitrification within a laboratory-scale Biological Aerated Filtration treatment system at 4 degrees C was investigated during an exposure time of approximately four months (acclimatized experiments). In addition, shock experiments from 20 degrees C to 4 degrees C and from 4 degrees C to 20 degrees C were performed. The acclimatized experiments demonstrated that the exposure time the system remained at low temperature strongly affects the rates of nitrification. Nevertheless, the experiments showed that significant nitrification rates are maintained for up to 115 days at 4 degrees C. The rate of ammonia removal after an exposure time of 115 days at 4 degrees C was shown to be as high as 16% of the rate of removal observed at 20 degrees C. The 20 degrees C to 4 degrees C shock experiment demonstrated a 56% decrease in the rate of ammonia removal. On the other hand, the 4 degrees C to 20 degrees C shock experiment demonstrated an increase in the relative rates of ammonia removal of up to 300% when compared to rates of removal measured after 115 days at 4 degrees C. Thus, although the rates of nitrification have been shown to decrease significantly as a function of exposure time at 4 degrees C, the process has demonstrated important rates of ammonia removal at 4 degrees C for the approximate span of the North American winter.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.004
Threshold uncertainty score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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 head0.008
GPT teacher head0.231
Teacher spread0.223 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations42
Published2009
Admission routes1
Has abstractyes

Explore more

Same venueWater Science & TechnologySame topicWastewater Treatment and Nitrogen RemovalFrench-language works237,207