Characterizing permafrost along the Alaska Highway, Southwestern Yukon, Canada
Bibliographic record
Abstract
The Alaska Highway through Southwestern Yukon is located in the discontinuous permafrost zone with many areas of the highway corridor associated with degrading permafrost. Given the strategic value of the corridor, it is critical to have a clear understanding of permafrost characteristics and distribution, particularly in the context of a changing climate. In the Beaver Creek area, the Alaska Highway traverses both glaciated and non‐glaciated terrain dating from the last glacial maximum. Permafrost characteristics are strongly influenced by regional glacial history, including the distribution of relict Pleistocene syngenetic permafrost. This thesis characterizes permafrost along the Alaska Highway between Beaver Creek and the Alaska border using a multidisciplinary approach. Our surveys include electrical resistivity tomography (ERT), airborne electromagnetics (AEM), geomorphological mapping, permafrost drilling, cryostratigraphic interpretations, geochemical analyses, and environmental monitoring to define the distribution and extent of permafrost within the study area. Using a combination of AEM and ERT data, we are able to define boundaries between non‐glaciated terrain and glaciated terrain, highlight regional bedrock geology, outline valley fill geometry, image the thermal impact of small and large scale surface water features, and estimate the depth of permafrost. Radiocarbon dating and stable isotope analyses of δ18O and δ2H combined with detailed cryostratigraphy highlight the ice‐rich nature of shallow Holocene permafrost and confirmed the presence of relict late Pleistocene ground ice at depth. The outcomes from this study will assist in the development of future mitigation strategies and maintenance plans for the highway.
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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 | 0.003 |
| Science and technology studies | 0.002 | 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".