Long-Term Monitoring of Mitigation Techniques of Permafrost Thaw Effects at Tasiujaq Airport in Nunavik, Canada
Bibliographic record
Abstract
This paper summarizes the long-term monitoring (2007–2018) of three test sections in the shoulder of the runway embankment of Tasiujaq Airport. The objective of this test site is to conduct a performance review of three permafrost protection techniques: gentle slope, air convection embankment (ACE), and heat drain. Each of these techniques and a reference section were installed on the side-slope of the embankment, over a length of 50 m. The results of 10 years of thermal monitoring have shown that the three methods tested have had positive effects on the thermal regime of the ground. While the convective techniques (ACE and heat drain) extracted enough heat from the ground to protect permafrost, the gentle slope was the most effective with a significant decrease in active layer thickness and ground temperature. In Tasiujaq, crosswinds during winter favour snow accumulation along the embankment; the gentle slope is the best option to minimize this effect and to limit the insulation of natural ground. Air convection and heat drain techniques are dependent on the temperature differential between ground and air to initiate convection. Therefore, those techniques are much more effective in regions where the temperature differential is greater.
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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 | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".