Calibration of a simple model for waste stabilisation pond performance in seasonal climates
Bibliographic record
Abstract
The paper describes the calibration of a model for waste stabilisation pond (WSP) performance in seasonal climates, based on the use of readily available climate data sets. Calibration data were taken from a wide geographical area of Canada and the USA, including coastal and moderately seasonal sites. Good agreement with measured values was shown using a biochemical oxygen demand (BOD) decay constant of 0.3 day(-1) for facultative ponds and 0.07-0.1 day(-1) for storage/maturation ponds with a temperature-related Arrhenius constant of 1.05, and a fixed BOD decay constant of 0.007 day(-1) at water temperatures below 0 °C. The results suggested that such models could potentially be used as the basis for WSP design guidelines tailored to a wide range of climatic conditions.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| 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 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| 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 teacher head, 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".