Case study of use of falling weight deflectometer to investigate railway infrastructure constructed upon soft subgrades
Bibliographic record
Abstract
Falling weight deflectometer (FWD) testing was conducted along with embankment and subgrade sampling over 210 km (130 miles) of Canadian National Railway’s Lac La Biche Subdivision, which runs between Edmonton and Fort McMurray, as a part of a larger investigation of the line for increased axle loads. The resulting measurements were evaluated for their ability to identify soft subgrades. Two analyses were conducted to this end. First, the statistical distribution of peak deflections recorded by the FWD was investigated for different types of subgrade material. Second, the properties of track substructure were studied by characterizing the deflection time histories using a dynamic model of a single mass on a viscoelastic foundation and least-squares curve fitting. Four characteristic types of deflection time histories were identified for differing substructure conditions. Simplified dynamic modelling of railway track substructure showed that where relatively thick embankment exists over subgrade, the response of track is overdamped behavior.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| 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".