Influence of snow on near-surface ground temperatures in upland and alluvial environments of the outer Mackenzie Delta, Northwest Territories<sup>1</sup>This article is one of a series of papers published in this CJES Special Issue on the theme of <i>Fundamental and applied research on permafrost in Canada</i>.
Bibliographic record
Abstract
Relations between snow cover, active-layer thickness, and near-surface ground temperatures were determined in 2005–2009 for a diverse range of alluvial and upland settings in the outer Mackenzie Delta. Here, the snow cover developed primarily by wind redistribution, with its spatial variation controlled by topography in uplands and vegetation height in alluvial lowlands. Snow cover was the primary influence on freeze-back duration and the mean annual temperature at the top of permafrost (TTOP), with the difference in median TTOP between alluvial (–3.7 °C) and upland (–6.1 °C) settings related to the greater snow depth and soil moisture in the alluvial plain. The active layer was generally deeper in the wet alluvial lowlands, where the average duration of active-layer freeze back (101 days) was nearly double the time taken in the well-drained uplands (55 days). The surface offset (ΔT S ; up to 11 °C) dominated the difference between annual mean air temperature (AMAT) and TTOP (ΔT). In alluvial terrain, ΔT S varied with snow depth, but in the uplands, ΔT S was more consistent from site to site. The small thermal offset (<2 °C) was slightly greater in alluvial terrain than in the uplands. The overall range in ΔT (2–10 °C) led to a range during the study of 7.2 °C in TTOP at the sites. The range in AMAT was 1.3 °C but up to 1.7 °C in TTOP at any one site. Permafrost was well established throughout the area except adjacent to channels where TTOP was close to 0 °C.
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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 | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".