Queen Elizabeth Islands: problems associated with water balance research
Bibliographic record
Abstract
The Queen Elizabeth Islands in Arctic Canada are in an extremely remote region with long, cold winters, and 2- to 3-month summers, with 24-h daylight. Snow is a major part of annual precipitation, but there are few Arctic weather stations and precipitation data accuracy is hampered by gauge undercatch. Large spatial variations in snowmelt and evaporation make it difficult to extend point calculations over a basin. Currently no official hydrometric station exists in the Islands and the short-term available records are afflicted by stream gauging problems during peak flows. Annual water balances are often not closed, as not all the components are measured or calculated; this applies to early studies and to all glacierized catchments. Given the sensitivity of polar regions to climatic change and the likely importance of freshwater input to the Arctic Ocean, performing proper water balances for the basins in the Arctic Archipelago is a challenge.
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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 | 0.012 | 0.033 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.008 |
| Science and technology studies | 0.004 | 0.003 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.012 | 0.004 |
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".