Hydrological connectivity and seasonal storage change of tundra ponds in a polar oasis environment, Canadian High Arctic
Bibliographic record
Abstract
Abstract Tundra ponds are a common type of wetland in the High Arctic. Their preservation is predicated upon ample water supply and storage to overcome evaporation losses. Two years of hydrological study of a cluster of ponds in a polar oasis of the Canadian Arctic showed the dominance of overland flow in the spring as an agent that recharged the pond storage. The freshet produced by snowmelt gave rise to extensive surface flow connections between the ponds and with their surrounding areas, but such flow connectivity lasted only about 2 weeks. After that, the ponds appeared to be separated from lateral drainage. Detailed mapping of the water and frost table positions together with water balance investigation, however, indicated the presence of subsurface flows between some ponds and with their adjacent slope. The flow magnitude was small relative to the vertical processes of evaporation and rainfall. Evaporation loss was mainly responsible for storage depletion, leading to a decline in pond level and shrinkage of open water area, unless major rain events restored the storage (as in 2006). It is postulated that climate warming could increase evaporation and active layer thickness to promote greater loss in surface water storage, or geomorphic processes could breach the pond rims, leading to the demise of ponds. Copyright © 2006 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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| 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".