The effect of initial smoothness on flexible pavement life
Bibliographic record
Abstract
The paper describes a procedure for estimating changes in pavement life span, attributed to changes in the initial smoothness, for asphalt concrete pavements in Ontario. The procedure takes into account the influence of initial smoothness and ride deterioration over time, as well as the influence of other distresses that may trigger the need for pavement rehabilitation. In this case, an improvement in initial pavement smoothness may not have a significant influence on extending the pavement life, because these sections fail and are rehabilitated before they reach terminal roughness. The challenge is to quantify the influence of initial smoothness on pavement life while recognizing the influence of other distresses. The procedure utilizes the observed occurrence of six key pavement distresses at the time of rehabilitation. These distresses include roughness, raveling, transverse cracking, rutting, alligator cracking, and other cracking. Expert judgment is used to quantify the impact of the initial smoothness on the six key pavement distresses. The effect of improved initial smoothness is expressed as the change in pavement life. The procedure yields a calibrated transfer function converting the change in initial smoothness into the change in pavement life.
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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 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".