Bibliographic record
Abstract
Warm Mix Asphalt is defined as a group of technologies that allow for a reduction in the temperatures at which asphalt mixes are produced and placed relative to traditional Hot Mix Asphalt (HMA). WMA is produced and placed at temperatures 20 to 50 deg C less than conventional HMA. The production and paving of asphalt at these reduced temperatures generates fewer emissions and requires less energy while maintaining or enhancing pavement performance. MTO began preliminary research on the application of WMA to Ontario roads in 2006, followed by initial WMA trial contracts in 2008. To evaluate the environmental benefits of WMA, MTO required additional tests and measurements be performed on several of the 2010 contracts. These included emissions measurements at both the asphalt manufacturing plant and paving site, temperature measurements of the WMA during production and paving, and additional tests to assess WMA pavement performance . In these trial contracts, WMA paving occurred at temperatures 10 to 30 deg C lower than conventional HMA without any adverse effects on asphalt properties. The WMA trials were successful and supported increased WMA usage. As a result, MTO decided to target 10 percent WMA use on contracts completed in 2011. In addition, MTO decided to include larger tonnages of WMA than in previous years, and to use WMA in both the binder course and surface course layers. This project was nominated for the TAC 2011 Environmental Achievement Award. For the covering abstract of this conference see ITRD record number 201211RT334E.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.012 | 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".