Terrain controls on the occurrence of coastal retrogressive thaw slumps along the Yukon Coast, Canada
Why this work is in the frame
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Bibliographic record
Abstract
Abstract Retrogressive thaw slumps (RTSs) are among the most active landforms in the Arctic; their number has increased significantly over the past decades. While processes initiating discrete RTSs are well identified, the major terrain controls on the development of coastal RTSs at a regional scale are not yet defined. Our research reveals the main geomorphic factors that determine the development of RTSs along a 238 km segment of the Yukon Coast, Canada. We (1) show the current extent of RTSs, (2) ascertain the factors controlling their activity and initiation, and (3) explain the spatial differences in the density and areal coverage of RTSs. We mapped and classified 287 RTSs using high‐resolution satellite images acquired in 2011. We highlighted the main terrain controls over their development using univariate regression trees model. Coastal geomorphology influenced both the activity and initiation of RTSs: active RTSs and RTSs initiated after 1972 occurred primarily on terrains with slope angles greater than 3.9° and 5.9°, respectively. The density and areal coverage of RTSs were constrained by the volume and thickness of massive ice bodies. Differences in rates of coastal change along the coast did not affect the model. We infer that rates of coastal change averaged over a 39 year period are unable to reflect the complex relationship between RTSs and coastline dynamics. We emphasize the need for large‐scale studies of RTSs to evaluate their impact on the ecosystem and to measure their contribution to the global carbon budget.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 it