Effects of Land Use on Flow Rate Change Indices
Bibliographic record
Abstract
The goal of this study was to analyze the impact of agriculture on the spatial and temporal variability of flow rate change indices from 1930 to 2008. The two indices used are the coefficient of immoderation (CI) and the coefficient of variation (CV). Values of these two indices are higher for the L’Assomption River agricultural watershed than for the Matawin River forested watershed due to higher runoff in the former than in the latter. The difference in these values between the two watersheds is greater for winter, but it is lower for summer, when the difference in runoff between the two watersheds is strongly attenuated by the presence of crops. Regarding the temporal variability, a difference between the two watersheds is observed in the fall. For the agricultural watershed, mean values of neither index show a break in slope, while a break is observed for the forested watershed. In both watersheds, both indices are positively correlated with maximum temperature and total rainfall in winter, but only to this latter climate variable in the fall. In springtime, the two indices are negatively correlated with minimum temperature in the forested watershed, but only CV is correlated, positively, with this same climate variable in the agricultural watershed.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| 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".