Extreme cold weather airfield damage repair testing at Goose Bay Air Base, Canada
Bibliographic record
Abstract
Rapid Airfield Damage Recovery (RADR) technologies have proven successful in temperate and subfreezing temperatures but have not been evaluated in extreme cold weather temperatures near 0°F. To address this capability gap, laboratory-scale and full-scale testing was conducted at these temperatures. Methods developed for moderate climates were adapted and demonstrated alongside methods that used snow harvested on-site as compacted backfill. After only a few days of training, seven experimental repairs were conducted by Canadian airmen at Goose Bay Air Base in Labrador, Canada, and load tested with a single-wheel C-17 load cart. Existing RADR technologies performed adequately despite the freezing temperatures, with the main tactic, techniques, and procedures modification being an increased cure time for the rapid-setting concrete surface material. Compacted snow-water slurry methods also performed well, demonstrating their ability to withstand over 500 passes of single-wheel C-17 traffic after sufficient freezing time.
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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 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 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".