Embankment evolution of a gravel road on permafrost terrain five years after construction: the Inuvik-Tuktoyaktuk Highway
Bibliographic record
Abstract
The Inuvik-Tuktoyaktuk Highway (ITH) is a 137-km gravel road constructed during winters 2014-17 using frozen materials from seven borrow sources for a fill-only embankment designed to protect underlying permafrost.Road-surface settlement has occurred with active layer development and consolidation, compounded by right-of-way edge effects.To explore the evolution of a gravel road embankment on permafrost five years after construction we: 1) examine active layer development in the road and undisturbed terrain; 2) assess embankment thicknesses by differencing 2021 Lidar elevations with the 2011 pre-construction terrain; and 3) summarize field observations of underlying ice-wedge thaw and remotely-sensed rates of road-surface subsidence.In 2021, embankment centerline thaw depths approximated using ground temperature data were estimated to range from 2.3 to 3.7 m, which exceeded seasonal thaw depths in the adjacent tundra by 5-fold.The Lidar-derived embankment thicknesses in 2021 were less than 1.5 m for about 58% of the road length, suggesting that the embankment may be thawed by the end of summer for approximately half of the road length.Ice-wedge subsidence recorded at 57 locations, was associated with thin embankments and more frequent in the northern half of the corridor, excluding the last 25 km where the ITH was constructed on a pre-existing borrow pit access road that likely thawed near-surface permafrost before ITH construction.Estimated road surface subsidence from the period August 2019 to August 2021 supports these patterns.The findings demonstrate the value of systematic collection and analyses of monitoring data on road-permafrost interactions to inform design and maintenance that maximizes safety and performance.1
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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 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".