An evaluation of hydrometric monitoring across the Canadian pan-Arctic region, 1950–2008
Bibliographic record
Abstract
This study evaluates the hydrometric monitoring maintained within the Canadian pan-Arctic and is based on the hydrometric gauges closest to northern seas for 76 river systems throughout 1950–2008. Monitoring is quantified by compiling time series of total gauged area and discharge values from the available hydrometric records. We further evaluate the quality of hydrometric data by examining the availability of hydrometric records, the continuity of individual records, and the influence of water regulation on river systems. The maximum gauged area of the Canadian pan-Arctic was 64% in 1990 before it slowly decreased to 56% in 2008. Larger river systems typically had the most hydrometric data available, though each river system had an average of 46% of their records available. In 1998, a maximum of 22 river systems had more than 30 years of continuous records, which is the maximum attained throughout the study period. For future improvements in hydrometric monitoring, additional gauges on relatively small rivers will need to be deployed. We suggest new gauges should be implemented in the Eastern Hudson Bay, Ungava Bay and Labrador Sea basins in spite of the tremendous need for more in the Arctic Archipelago.
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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 | 0.003 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.007 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".