Spatial and temporal dynamics of groundwater flow across a wet meadow, Polar Bear Pass, Bathurst island, Nunavut
Bibliographic record
Abstract
Interest is growing about how groundwater supplies will shift in warming northern terrains. We evaluated the seasonal and spatial pattern of groundwater flow in a wet meadow bordered by a late-lying snowbed and tundra ponds at Polar Bear Pass, Bathurst Island (75.7°N, 98.7°W). A water budget approach signalled the relative importance of groundwater inflow to tundra ponds. Groundwater flow across the wet meadow was estimated using a modified Darcy's equation, which requires information on both water and frost tables, and hydraulic conductivity. These data were obtained from 2007 to 2009 along a series of water wells extending from a late-lying snowbed across the wet meadow to a nearby study pond. Groundwater fluxes across the wet meadow were limited in magnitude and duration in a warm/dry year (2007), when the late-lying snowbed was the main external water source, a response differing from rainy/cool years (2008 and 2009). Overall, seasonal water budgets indicate that groundwater fluxes were minimal in the wet meadow and an adjacent tundra pond. Late-lying snowbeds play a limited role in sustaining wet meadows and ponds here. Summer precipitation and evaporation continue to drive wet meadow and tundra pond hydrological response in low-gradient wetlands, especially in the post-snowmelt season. Copyright © 2016 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 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 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".