Cold climate hydrological flow characteristics of constructed wetlands
Bibliographic record
Abstract
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.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".