Department of Transportation Perspective: A Survey on Polyphosphoric Acid Use and Issues
Bibliographic record
Abstract
To establish a reference point in time, Dean Maurer of the Pennsylvania Department of Transportation (DOT) conducted a survey of the state DOTs to determine their current specification requirements with respect to the use of polyphosphoric acid (PPA). This survey was conducted in the winter of 2008–2009. The survey had 37 responses from the state DOTs. The Ontario Ministry of Transport (MTO) had also conducted a survey in 2007 on the use of PPA to modify asphalt binder. Pennsylvania combined the data from the two surveys to achieve a combination of 48 responses. The survey overall provided a snapshot in time on the use of PPA and the general policies of the highway agencies on its use. The general conclusions from the survey were the following: There is a wide spectrum in the use of PPA from outright bans to unrestricted use; No specific documentation of poor performance was brought forward; A potential exists to significantly expand the currently limited performance database and available documentation on PPA as a binder modifier; Due to fluctuating binder–modifier supply, agencies will need to be more flexible and knowledgeable concerning modifiers; and The workshop agenda should go a long way toward filling critical gaps in knowledge on PPA modification.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.004 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.011 | 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".