Frequency and magnitude of active‐layer detachment failures in discontinuous and continuous permafrost, northern Canada
Bibliographic record
Abstract
Abstract Active‐layer detachment failures triggered weeks to months after forest fire in the central Mackenzie Valley (65°N, discontinuous permafrost zone) are compared to others generated almost immediately by summer meteorological conditions on the Fosheim Peninsula, Ellesmere Island (80°N, continuous permafrost zone). Preferred long‐axis orientations in both zones vary in relation to valley geometry and ground ice distribution: differential insolation plays no direct role in detachment failure distribution. Rates of geomorphic work over periods of one to two centuries are of the same order of magnitude. Threshold meteorological conditions for initiating failures on the Fosheim Peninsula can be incorporated into a surface heating index, but pre‐conditioning of the active layer remains important because rapid thaw does not always initiate activity. Slope pre‐conditioning does not occur at the fire‐affected sites because the failure zone is within formerly perennially frozen ground. Long‐term rates of unit vertical transport at the most active site on the Fosheim Peninsula are similar to those due to debris flow and slushflow in a nearby mountain range. The frequency of potential triggering events at the Ellesmere Island sites is expected to increase if summer climate warms, providing low percentage cloud cover is maintained during periods of high air temperatures. Copyright © 2005 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 | 0.001 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 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".