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Record W2030405362 · doi:10.2166/wst.2009.332

Hydraulic performance of a mature wetland treating milkhouse wastewater and agricultural runoff

2009· article· en· W2030405362 on OpenAlexaffabout
Sean Speer, Pascale Champagne, Anna Crolla, Chris Kinsley

Bibliographic record

VenueWater Science & Technology · 2009
Typearticle
Languageen
FieldEnvironmental Science
TopicConstructed Wetlands for Wastewater Treatment
Canadian institutionsUniversity of GuelphQueen's University
Fundersnot available
KeywordsTRACERWetlandEnvironmental scienceSurface runoffHydrology (agriculture)InflowVegetation (pathology)Constructed wetlandOutflowHydraulicsWastewaterSedimentFlow (mathematics)Environmental engineeringGeologyEcologyGeotechnical engineeringEngineeringGeomorphology

Abstract

fetched live from OpenAlex

A tracer study is an efficient method of determining flow dynamics within a constructed wetland. In previous studies, a number of tracer studies have been carried out on various constructed wetlands covering a wide range of configurations. From these tracer studies it is evident that all constructed wetlands perform differently and generally with less efficiency than assumed by theoretical design computations. During the summer of 2004, a tracer study was performed on a constructed wetland located in Embrun, Ontario (Canada) treating milkhouse wastewater and agricultural runoff to determine its actual hydraulic performance. Sediment height and vegetation density profiles were also obtained and examined to explain the preferential flow pathways that were observed during the tracer analysis. It was determined that the constructed wetland had an effective treatment area representing 79% of the total area, and that the hydraulic efficiency of the system was 74%. Examination of the sediment height and vegetation density profiles resulted in no evidence of physical pathways that could be attributed to the establishment of preferential flow. The hydraulic efficiency was therefore attributed to the inflow and outflow layout of the constructed wetland cell, combined with wind induced mixing.

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 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 score0.015
Threshold uncertainty score0.483

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.003
GPT teacher head0.183
Teacher spread0.180 · 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 teacher head, 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

Citations16
Published2009
Admission routes2
Has abstractyes

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