Comparison between France and Quebec backanalysis methods of deflection measurements
Bibliographic record
Abstract
The Laboratoire Central des Ponts et Chaussees (France) and the Ministere des Transports du Quebec (Canada) have developed a joint research project on the behavior ofroadways during severe frost conditions. This project aims to increase understanding about fatigue damage and their diminished load-bearing capacity under the combined effect oftraffic and frost-thaw cycles.An experimental pavement was built in Quebec in 1998 and its behav ior was monitored for six years. Pavements with a cement-treated base and a hot-mix asphalt base were selected.Two test beds of each type were constructed. One of each two test beds was thermally insulated by a layer of extruded polystyrene, to d istinguish traffic and climate effects.This paper compares France and Quebec backanalysis methods of deflection measurements of the two uninsulated test beds. It describes :- the experimental site (pavement structures, weather conditions and surveys),- the surface deformability measurements with a Benkelman test truck (inclinometer) for the LCPC and FWD for the MTQ- the determination of moduli values by backanalysis of deflection measurements on test beds 1 and 4, and the differences and the difficulties met with French and Quebec methods.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| 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".