Massive Ice Control on Permafrost Coast Erosion and Sensitivity
Bibliographic record
Abstract
Abstract High overall rates of permafrost cliff retreat, coupled with spatial variability, have been accompanied by increased uncertainty over future landscape dynamics. We map long‐term (>80 years) retreat of the shoreline and photogrammetrically analyze historic aerial imagery to quantify the processes at a permafrost coast site with massive ground ice. Retreat rates have been relatively constant, but topographic changes show that subsidence is a potentially critical but often ignored component of coastal sensitivity, exceeding landward recession by over three times during the last 24 years. We calibrate novel passive seismic surveys along clear and variable exposures of massive ground ice and then spatially map key subsurface layers. Combining decadal patterns of volumetric change with new ground ice variation maps enables past trends to be interpreted, future volumetric geomorphic behavior to be better constrained, and improves the assessment of permafrost coast sensitivity and the release of carbon‐bearing material.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 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) | 0.002 | 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".