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Record W6921900454 · doi:10.7939/r3p952

Sulphide Production and Management in Municipal Stormwater Retention Ponds

2014· dissertation· en· W6921900454 on OpenAlexaboutno aff

Bibliographic record

VenueUniversity of Alberta Library · 2014
Typedissertation
Languageen
FieldEnvironmental Science
TopicFecal contamination and water quality
Canadian institutionsnot available
Fundersnot available
KeywordsStormwaterSurface runoffRetention basinNitrateSedimentWater qualityHydrogen sulphide

Abstract

fetched live from OpenAlex

Municipal stormwater retention ponds are a means of managing stormwater in urban settings. Due to the temporal and spatial variations involved with stormwater, numerous contaminants find their way in stormwater retention pond, creating various problems to mitigate against. The City of Edmonton owns a stormwater pond that has historically produced higher levels of hydrogen sulphide. A field study was completed in the City of Edmonton, comparing two stormwater retention ponds in terms of water quality and sediment microbial communities to understand differences in biological degradation that would encourage sulphate reduction, believed to stimulate the production of hydrogen sulphide. The field study comparison was followed by laboratory studies focused on means of suppressing sulphide production. Nitrate amendments were effective in suppressing sulphate reduction; however the addition of a carbon source stimulated greater sulphide production. Extracts from Serrano peppers were also tested as a biocide and inhibitor for sulphate reducing bacteria.

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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.031
Threshold uncertainty score0.062

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0010.000
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 head0.009
GPT teacher head0.190
Teacher spread0.181 · 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 designObservational
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

Citations0
Published2014
Admission routes1
Has abstractyes

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