Comparison of Network Level Recommendation and Project Level Rehabilitation Treatment for Pavement (Poster)
Bibliographic record
Abstract
Alberta Transportation (AT)’s mandate includes managing the provincial highway network with over 32 thousand kilometers in total length that covers highway classes from the National Highway System to the local roads. AT has been utilizing a computerized pavement management system (PMS) for the management of the Alberta’s provincial pavement network since the early 1980’s. The PMS database contains historical “As-built” construction data as well as measured performance data, such as distress ratings, IRI/Rut depth and the deflection (FWD) test results. The PMS implemented within HPMA allows AT to configure the database and conduct analyses to produce multi-year pavement rehabilitation recommendation lists (Network Level recommendations with location, treatment and need years). Once a pavement rehabilitation project proceeds to the design stage, it is expected that the decisions made at the project level may differ from the treatment recommended at the network level. This study is focused on the differences and/or similarities between the recommended activities at the Network Level, based on the pavement condition data collected each year, and historical “As-built” pavement information, which reflects the final design for pavement treatment activities (Project Level).
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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 | 0.004 | 0.020 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.010 | 0.002 |
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".