Cataloguing Retrogressive Thaw Slumps along the Old Crow River, YT: Proposing Regional Controls on Retrogressive Thaw Slump Formation and Growth
Bibliographic record
Abstract
The Old Crow River flows across a continuous permafrost zone in the Northern Yukon. The seasonally frozen ground contains ice, organics, and metal pollutants. Retrogressive thaw slumps form when permafrost on the riverbanks thaw and sediment flows downslope into the river, leaving an unvegetated scar that can be seen on satellite images. The thaw slump will grow rapidly until stabilization impedes further melt. The specific controls on permafrost thaw will vary regionally throughout the Yukon, and the variables affecting formation and activity of thaw slumps along the Old Crow River have not been studied. Influences on the activity of thaw slumps are proposed through cataloguing geomorphic conditions and variables measured using satellite images and digital elevation data. The data collected suggests that cliff slope and direction, river processes, and proximity to certain landforms may influence growth and activity of thaw slumps along the Old Crow River. Satellite data is used to perform a supervised classification of the area that identifies RTS with a sensitivity of 62% and precision of 85%. Department: Physical Sciences Faculty Mentor: Dr. Robin Woywitka
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 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".