Enhanced Prairie Wetland Effects on Surface Water Quality in Crowfoot Creek, Alberta
Bibliographic record
Abstract
Abstract A three-year study was conducted to examine the effects of a prairie wetland enhanced for waterfowl habitat on surface water quality in the Crowfoot Creek watershed in southern Alberta, Canada. Monitoring was carried out at the Hilton wetland from mid-March to the end of October in 1997 to 1999 at two inflow sites and one outflow site. Data were collected on flow, total phosphorus (TP), total nitrogen (TN), total suspended solids (TSS), and fecal coliform (FC) bacteria. Nutrient concentrations were highest in the spring, and decreased during the remainder of the monitoring period each year. Nutrient concentrations did not change significantly within the wetland due to the form of nutrient, reduced retention times for nutrient uptake, and the addition of nutrients to the water through sediment release and decomposition of organic matter. The wetland acted as both a source and a sink for nutrients, depending on flow volumes. TSS concentrations decreased significantly from inflow to outflow, indicating sedimentation occurred in the wetland. FC bacteria levels were lowest in the spring and increased during the post-spring runoff (PSRO) period. FC bacteria counts decreased significantly within the wetland throughout the entire year. The Hilton wetland was effective in reducing the amounts of TSS and FC bacteria exported from the wetland; however, there was no significant change in nutrient status.
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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 | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 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".