Landscape Evolution Triggered by Polycyclic Thermokarst on Herschel Island, Yukon Territory
Bibliographic record
Abstract
Retrogressive thaw slumps are a common thermokarst landform in areas of ice-rich continuous permafrost characterized by large massive ground ice bodies, often several metres thick and hundreds of metres in extent. These features can retreat inland by as much as 15-20 metres annually (Figure 1) and are thus one of the most important carbon sources along Arctic coastlines. In locations like Herschel Island and the Yukon Coastal Plain, there are numerous active and stabilized thaw slumps (e.g. Lantuit and Pollard, 2008). In many cases, the new slumps form in the floor of a stabilized slump, leading to polycyclic thermokarst behaviour. Previous periods of thermokarst and retrogressive thaw slump activity can be identified morphologically and stratigraphically, as well as through changes in vegetation patterns (e.g. Cray and Pollard, 2015). Former slumps are usually marked by open vegetated depressions with a well-defined (low) head scarp that faces downslope. The headwall of an active slump provides natural permafrost exposures from which considerable cryostratigraphic information can be obtained. In the case of a polycyclic retrogressive thaw slump, the previous cycle of thermokarst is marked by a well-defined thaw unconformity and truncated structures (e.g. ice wedges) overlain by massive debris flow deposits containing blocks of organic material. However, the polycyclic nature of slumps and how one episode may impact another are not fully understood. \n \nThe objectives of this project are to: 1) Visualize 3D landscape evolution changes related to polycyclic thermokarst for multiple slumps on Herschel Island from 2004 to 2013; and 2) Investigate and compare the polycyclic thermokarst behaviour between the slumps using a combination of cryostratigraphic, ground-penetrating radar, electrical resistivity, and biogeographic datasets of vegetation succession following disturbance (Cray and Pollard, 2015). \n \nThe landscape evolution models are generated by comparing the annual headwall positions of the slumps (2004-2013) recorded using differential GPS to a LIDAR base image captured in 2013. The ground-penetrating radar and electrical resistivity surveys highlight the geomorphic details of a former slump’s transition from an active to stabilized state, as well as provide insight into the thickness and extent of the debris flow deposits and ground ice units for different episodes of polycyclic thermokarst.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| 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".