The Impact Of Wetlands On Flood Control In The Red River Valley Of Manitoba
Bibliographic record
Abstract
This document serves to investigate the role that wetlands play in flood control. The limitations of this report, however, must be recognized. The results and conclusions drawn in this report are based on one low frequency flood year, 1997. Additionally, the impacts of wetlands are generalized for the entire Red River Basin, based on those results from one representative watershed, the Rat River. The availability of data also limited the choice of the modeling tool, in addition to the sub-routines that could be used within the model. The results generated from this study contribute to the correct estimation of the reduction of flood related damages, in that the findings can be used to assist in determining "possible actions to eliminate or reduce long-term risk to human life and property due to flooding" (International Red River Basin Task Force 1997). Additionally, these results will aid in the evaluation of whether changes to non-structural flood control measures are 3 necessary. This study will also contribute to the investigation of watershed land use changes in that the final results will help determine the extent to which "local and possibly regional effects on timing, magnitude, and volume of peak flows" (ibid. 1997) resulted from these changes. 4
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".