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Record W2277702982

Pocket Wetland Impacts on Stormwater Runoff and Water Quality

2015· dissertation· en· W2277702982 on OpenAlexaboutno aff
Jason Krompart

Bibliographic record

VenueThe Atrium (University of Guelph) · 2015
Typedissertation
Languageen
FieldEnvironmental Science
TopicUrban Stormwater Management Solutions
Canadian institutionsnot available
Fundersnot available
KeywordsStormwaterSurface runoffEnvironmental scienceWetlandWater qualityStormwater managementWater resource managementLow-impact developmentEnvironmental engineeringHydrology (agriculture)Environmental planningEngineeringEcologyGeotechnical engineering
DOInot available

Abstract

fetched live from OpenAlex

Impervious surface areas within an urban catchment can generate higher runoff volumes and degrade water quality in local streams. Pocket wetlands are an end-of-pipe stormwater management system that detain runoff and improve stormwater quality before entering the channel. These wetlands are used as a ‘polishing’ feature in stormwater management systems. The working hypothesis is that a pocket wetland will attenuate flow and improve water quality, which can be modeled with an areal decay model. Stormwater runoff and water quality was monitored upstream, downstream and at the inlet of a wetland in the Churchville subwatershed in Brampton, ON, April – October 2014. Results indicate the wetland provided short-term storage for the remediation of water quality through rainfall events, which were then estimated using an areal decay model. This study provides evidence on the performance of pocket wetlands for stormwater management and design.

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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.047
Threshold uncertainty score0.094

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 studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.000

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 head0.021
GPT teacher head0.238
Teacher spread0.216 · 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
Published2015
Admission routes1
Has abstractyes

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