Review of Effectiveness and Costs of Strategies to Improve Roadbed Stability in Permafrost Regions
Bibliographic record
Abstract
This paper reviews the effectiveness and costs of strategies to improve roadbed stability in permafrost regions, based on a synthesis of literature findings. Roadbeds in permafrost regions experience instability when the embankment loading and its heat absorption properties degrade the permafrost foundation. A variety of engineering strategies are used to mitigate this effect. The review summarizes the rationale, effectiveness, and costs of four types of strategies, namely those that control roadbed thawing, cool the roadbed, insulate the roadbed, and reduce roadbed fill weight. The literature reveals that strategies to control roadbed thawing, insulate the roadbed, or reduce roadbed fill weight do not reverse the long-term degradation of permafrost foundations. Strategies that cool the roadbed by implementing air convection embankments, ventilation ducts, thermosiphons, heat drains, or combinations of these are effective in reducing embankment temperatures and stabilizing the roadbed. Costs vary by geographic and climatic conditions and the proximity of materials to the construction site. Reported data suggest that conducting normal maintenance is less expensive than implementing roadbed cooling strategies, but maintaining serviceability may not be feasible.
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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 | 0.005 | 0.017 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.003 |
| Bibliometrics | 0.005 | 0.006 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
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".