Batagay megaslump: A review of the permafrost deposits, Quaternary environmental history, and recent development
Bibliographic record
Abstract
Abstract The Batagay megaslump, in the Yana Uplands of northern Yakutia, Russia, is the largest known retrogressive thaw slump in the world. The slump exposes a remarkable sequence of Ice Age permafrost deposits that record the interaction of colluvial, eolian and periglacial processes on a hillslope episodically forested during the last 650 ka or more in response to climate variability on glacial–interglacial timescales. Numerous bones, teeth, and occasional carcasses of Pleistocene and Holocene mammals have been recovered from the permafrost. The megaslump developed over the course of several decades in three stages: (1) gullying, (2) thaw slumping, and (3) megaslumping. After disturbance to the taiga vegetation cover in the 1940s–1960s, a hillslope gully formed by the early 1960s. The gully initiated thaw slumping along its central part during the 1980s, with the slump enlarging to megaslump (>20 ha) proportions during the 1990s. By 2019, the area of the slump had reached about 80 ha and its headwall above the slump floor was up to about 55 m high. The main geomorphic processes of slump growth are headwall ablation and thermal erosion, producing a distinctive terrain of icy badlands on the slump floor. Though much of the megaslump is rapidly growing at present, it will probably stabilize eventually as an irregular terrain characterized by sandy ridges and sand‐filled elongate depressions formed by degradation of the badlands. Comparison of the Batagay megaslump with megaslumps from northwest Canada reveals several similarities and differences in terms of their geomorphology, permafrost deposits, and Quaternary history.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.007 | 0.009 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".