Bibliographic record
Abstract
Peat filters have been used to treat septic tank effluents from domestic and commercial sources, landfill leachate, and acid mine drainage. A better understanding of the hydraulics and impact of the organic loading on these types of systems will enhance the application of peat filter systems. This paper presents the results of a field study to evaluate the hydraulics of a peat filter used to treat the septic tank effluent from a public school west of Ottawa, Ontario, Canada. The filter was instrumented with tensiometers and transducers to monitor the pore-water pressures in response to a pulse of septic tank effluent. Samples of peat were collected to determine the dry density profile with depth. The soil moisture retention curve, effective porosity, and hydraulic conductivity as a function of dry density were determined in laboratory experiments. A one-dimensional unsaturated flow model was used to predict the pressure response due to a pulse. Two model scenarios were evaluated to demonstrate the impact of density variations on model simulations. Model simulations that accounted for dry density variations with depth measured in the field more accurately simulated the pressure responses measured in the field.Key words: unsaturated flow, peat, filters, septic, modelling, density.
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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 | 0.001 |
| 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) | 0.000 | 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".