Occurrence and magnitude of low flows for Canadian rivers: an ecozone approach
Bibliographic record
Abstract
Low-flow occurrence and magnitude have been documented for Canada using the National Ecological Framework. The low flow database is composed of the 7-day low flow with 2-year return period (7Q2) values for 453 natural flow hydrometric stations with record lengths of at least 30 years; drainage areas ranged from 10 to 30 000 km2. Occurrence zones corresponding to predominant season for annual low flows are associated with ecozones. The ecozone scale was found to be suitable for regional analysis for several ecozones. For some ecozones there were insufficient data for regional analysis and for others finer resolution is required. Regional regression equations were developed for estimating 7Q2 in terms of area for ecozones containing at least 20 stations. The results of this work will help practitioners to identify the season of low flow occurrence and the appropriate method of analysis, and provide a means of estimating 7Q2 for ungauged sites for some ecozones.
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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 | 0.001 |
| Bibliometrics | 0.013 | 0.011 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 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".