Results from an instrumented highway embankment on degraded permafrost
Bibliographic record
Abstract
Roads and highways in Northern Manitoba are negatively affected by settlement of embankments in areas of degraded or degrading permafrost, particularly where the permafrost is locally discontinuous with mean annual temperatures close to 0oC. Changes in temperature lead to thawing, settlements of road surfaces and shoulders, and lateral spreading. These can cause potentially dangerous trafficability issues. The highway embankment in this research project is 18 km northwest of Thompson, Manitoba. Research involves field instrumentation, data collection, laboratory testing, and numerical modeling. This paper reports data collected from the field instruments and numerical modeling during the first 18 months of operation. RESUME Les routes dans le Nord du Manitoba sont negativement affectees par le tassement des digues dans les regions degradees par le permagel, explicitement ou le permagel est localement discontinu avec une temperature moyenne annuelle pres de 0C. Le changement en temperature resulte dans la decongelation, le tassement des surfaces et des accotements et le deplacement lateral. Ces derniers peuvent creer des problemes de traficabilite dangereux. La digue discutee se trouve a 18 km au nord-ouest de Thompson, Manitoba. La recherche comprend des instruments d’observation, la collecte de donnees, des epreuves de laboratoire et de la modelisation numerique. Les resultats de ce papier sont accumules par les instruments d’observation et de la modelisation numerique durant les premiers dix-huit mois d’activite.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 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".