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Record W2285819918

Cold climate hydrological flow characteristics of constructed wetlands

2005· article· en· W2285819918 on OpenAlexaboutno aff
E. Smith, Robert J. Gordon, A. Madani And G. Stratton

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEnvironmental Science
TopicConstructed Wetlands for Wastewater Treatment
Canadian institutionsnot available
Fundersnot available
KeywordsWetlandEnvironmental scienceHydrology (agriculture)Subsurface flowHydraulicsTRACERWastewaterConstructed wetlandEnvironmental engineeringMixing (physics)GeologyGroundwaterEcologyGeotechnical engineeringEngineering
DOInot available

Abstract

fetched live from OpenAlex

Smith, E., Gordon, R., Madani, A. and Stratton, G. 2005. Cold climate hydrological flow characteristics of constructed wetlands. Canadian Biosystems Engineering/Le genie des biosystemes au Canada 47: 1.11.7. Hydraulic tracers provide a means of estimating retention times (RTs) of constructed wetlands. The removal of pollutants by these systems is closely associated with their RTs. Better understanding RTs under a range of conditions should therefore help to provide insight into the overall treatment efficiencies offered by on-farm wetlands. The objective of this investigation was to estimate RTs in two similar surface flow agricultural constructed wetlands during high flow periods (i.e. April and January) and compare them to their theoretical retention times (TRT) based on plug flow hydraulics. Two side-by-side wetlands were evaluated and operated at different depths. Both systems were loaded with dairy wastewater at a rate of 50 kg of BOD5 had. Bromide was used as the tracing element and was pulse injected into each wetland. Results demonstrated that RTs were 50 to 60% of the TRT. Bromide appears to be a suitable ionic tracer for non-growing season wetland studies. Mass recoveries of the tracer ranged from 72 to 81%. Only 50 to 65% of the volume in these systems was considered to be active, indicating that there needs to be more uniform mixing. Flow conditions however, appeared to be good in both ice covered and unfrozen conditions.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.117
Threshold uncertainty score0.990

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0110.001

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 head0.006
GPT teacher head0.199
Teacher spread0.193 · 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.

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

Citations37
Published2005
Admission routes1
Has abstractyes

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