Hillslope hydrological linkages: importance to ponds within a polar desert High Arctic wetland
Bibliographic record
Abstract
Arctic wetland environments are considered to be sensitive to ongoing climate change but they have received limited attention despite their ecological importance. To understand and quantify better the hydrologic processes which are leading to the sustainability and demise of High Arctic ponds, a water balance framework was employed on several ponds situated in two broad geomorphic areas near Creswell Bay, Somerset Island (72°43′N, 94°15′W). These ponds are also linked to an upland area through a range of linear features: stream, late-lying snowbeds and frost cracks. This study assesses the importance of these features with respect to the sustainability of these wetland ponds. A pond's position in the moraine landscape was important in determining its connectivity to a nearby stream and late-lying snowbed. Close proximity to a stream draining a large upland snow-covered catchment ensures steady water levels during the snowmelt period. Once discharge slows, a late-lying snowbed continues to supply the pond and others nearby with meltwater. The deeply thawed, sandy coastal zone is characterized by frost cracks, which contribute to the patterned ground of this wetland zone. These cracks, when situated downslope of ponds, function primarily as ‘sinks’ and serve to deprive small and medium-sized ponds of water during dry periods, often leading to their desiccation.
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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 | 0.001 |
| 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 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".