Bibliographic record
Abstract
The sustainable life-cycle performance and cost effective preservation of the world's road networks is an increasing challenge. Hot in-place recycling (HIR) of functionally deteriorated, but still structurally sound, asphalt pavements is a cost-competitive alternative process, of potentially equivalent quality and performance, with less road-user disruption, compared to hot-mix asphalt (HMA) overlay and milling/HMA filling processes. The Martec AR2000 third generation HIR process is based on a recirculating forced hot-air with low-level radiant heating, processing (hot milling), post heating, drying, mixing, paving, and compaction system. This AR2000 third generation HIR system effectively deals with the recycling depth, heater efficiency and effectiveness, speed and productivity, emissions, and processing uniformity problems associated with previous second generation HIR systems. Monitoring of AR2000 HIR projects, particularly Ontario Highway 401, has shown good performance, better than second generation HIR, microsurfacing, and milling/filling with new or recycled HMA. With the use of more long-life asphalt pavements, and the recognition of top-down cracking surface distress, HIR should have an increasing role in asphalt pavement renewal. This will also involve associated asphalt technology advances such as Superpave, polymer modification, rejuvenator characterization and selection, and performance evaluation of the mix, in an overall systems approach to optimized HIR. For the covering abstarct of this conference see ITRD number E215163. (A)
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.013 | 0.006 |
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".