Snowpack–Vegetation–Terrain Relationships Across the Arctic Treeline, Churchill MB
Bibliographic record
Abstract
The arctic treeline at churchill is a 10-km-wide ecotone from open tundra to upland white spruce and lowland black spruce forest. Characteristics of the snowpack include depth, density, snow water equivalent, and heat transfer coefficient measured over two years during mid-winter. These studies reveal differences induced by vegetation variations and associated microclimates. As expected, mid-winter snowpack varies considerably between open tundra and forest sites. Despite the dramatic differences in canopy, the post-fire forest snowpack differed little from that of the unburned forests. In the peatlands, depressions associated with degrading ice wedges had snowpack characteristics more similar to forested sites than adjacent polygon centers. Interannual variations were much less than intersite variations in most snowpack characteristics. These studies are intended to be repeated annually in order to establish a longitudinal study of snowpack variation across the arctic treeline during a period of predicted dramatic change in climate.
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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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".