Plate testing of reinforced ice in the context of winter roads: experimental set-up and preliminary results
Bibliographic record
Abstract
Winter road networks generally comprise segments that run over land and over floating ice (rivers and lakes). The latter commonly are weak links in these operations, especially in a warming climate, because they rely on cold temperatures to achieve a thickness that is safe enough for the intended traffic. A testing program was designed to investigate the performance of steel cables and a polypropylene geogrid as reinforcement materials. This paper reports on the first stage of the test program, which was to design and implement a procedure to generate that information. One ice sheet was grown from freshwater in the NRC ice tank facility in Ottawa, and was partitioned into a series of eight plates 100 mm in average thickness. Forces and displacements were recorded while a downward vertical load was exerted on the plate at a constant displacement rate. Cracking activity was monitored via an acoustic sensor system. All plates underwent radial cracking. A good correlation existed between the response of the vertical load and cracking activity. Prospective follow-up on this preliminary testing is discussed.
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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 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".