The Nisku Test Road: Direct Measurement of the Impact of Heavy Loads onThin Membrane Pavements
Bibliographic record
Abstract
The purpose of this paper is to describe the Nisku Test Road in Alberta while discussing its purpose, breaking down its components and analyzing results. The test road is intended to monitor the pavement response under heavy oilfield cranes on thin membrane asphalt pavement and consists of three sections: thin asphalt wearing course, bituminous surface treatment and granular surface. The different sections were constructed so that strain at the bottom of the asphalt layer, surface deflection, and subgrade pressures could be determined while measuring temperature and moisture profiles. Avenues of testing using this road include Field testing involve controlled speed experiments of standard axle configurations and heavy axle vehicles with and without hydraulic suspensions. This paper presents the results from the first two cycles of testing at the site where heavy vehicles were tested in an attempt to understand the impact of these large vehicles on thin membrane pavements. The tests are part of a long term study to evaluate pavement performance and to develop load equivalency factors.
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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 | 0.001 | 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) | 0.002 | 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".