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Record W2322903761 · doi:10.2166/wqrjc.2013.020

Pollutant removal efficiency of a retrofitted stormwater detention pond

2013· article· en· W2322903761 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 Quality Research Journal · 2013
Typearticle
Languageen
FieldEnvironmental Science
TopicUrban Stormwater Management Solutions
Canadian institutionsUniversité Laval
Fundersnot available
KeywordsStormwaterPollutantEnvironmental scienceSurface runoffDetention basinRetention basinEnvironmental engineeringRetrofittingTotal suspended solidsSuspended solidsFirst flushPollutionHydrology (agriculture)WastewaterChemical oxygen demandEngineeringChemistryEcology

Abstract

fetched live from OpenAlex

The objectives of this study were to characterize the stormwater runoff for a residential catchment, evaluate the present detention pond removal efficiency for different pollutants, and evaluate how its efficiency can be increased by controlling the pond stormwater retention time. The analysed pollutants were total suspended solids (TSS), total metals and ammonia. Runoff pollutant concentrations were generally found to agree with literature for the small residential catchment. The design of the original pond was such that low retention times of most analysed pollutants occurred, causing a lower than expected removal efficiency when compared to similar types of ponds. The retrofitting of the pond consisted of adding a sluice gate at the outlet in order to retain stormwater for longer periods of time. The retrofit allowed drastic improvement of the removal efficiency for TSS, NH3-N and zinc, from 39 to 90%, 10 to 84%, and 20 to 42%, respectively.

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)0.006
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.780
Threshold uncertainty score0.997

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0060.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0000.001
Open science0.0010.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0130.004

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 head0.084
GPT teacher head0.351
Teacher spread0.267 · 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