Bibliographic record
Abstract
Abstract This study investigated the spatial scaling properties of Canadian flood flows, namely, annual maximum mean 1‐, 5‐ and 7‐day flows using both the product moments (PMs) and probability weighted moments (PWMs). Both approaches demonstrate that flood flows in climatic regions 1 (Pacific), 2 (South British Columbia mountains), 3 (Yukon and northern British Columbia), 6 (Northeastern forest), 7 (Great Lakes and St. Lawrence rivers), 8 (Atlantic), and 10 (Arctic tundra) exhibit simple scaling with scaling exponent θ/H close to 0·90, while flood flows in regions 4 (Prairie provinces), 5 (Northwestern forest), and 9 (Mackenzie) does not with scaling exponent θ/H close to 0·50. The plots of coefficient of variations of flood flows versus drainage area indicate that Cv remains almost constant in regions 1, 2, 3, 6, 7, 8, and 10, while it decreases as drainage area increases in regions 4, 5, and 9. These results demonstrate that the index flood method is applicable in climatic regions 1, 2, 3, 6, 7, 8, and 10, while it is not in climatic regions 4, 5, and 9. The physical backgroud of the simple scaling of flood flows in most Canadian climatic regions is that snowmelt or rain‐on‐snow runoff is a dominant flood‐generating mechanism across the country. Copyright © 2008 John Wiley & Sons, Ltd.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| 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".