Variation in Water Quality of a Stormwater Pond from Diurnal Thermal Stratification
Bibliographic record
Abstract
The city of Calgary, Canada, has considered reusing stormwater from detention ponds for the irrigation of public lands. The diurnal variability in the water quality of these ponds was studied to ensure public safety. Field observations of diurnal thermal stratification and diurnal variation in water quality were conducted in a stormwater pond during the 2007 irrigation season normally from late June to September. Diurnal thermal stratification occurred in the upper water column, from the surface to approximately 1.2 m in depth. Diurnal variations in microorganisms involved high concentrations during the day and low concentrations at night. Increases in physicochemical water quality parameters at night were observed at the bottom of the water column, at a depth of 1.0 m. Observations suggest that the effects of diurnal thermal stratification alter pond hydrodynamics, and thus, alter the diurnal variation of water quality in turn.
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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 | 0.001 | 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) | 0.000 | 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".