MATERIALS AND PROCEDURES FOR REPAIR OF POTHOLES IN ASPHALT-SURFACED PAVEMENTS -- MANUAL OF PRACTICE
Bibliographic record
Abstract
The Strategic Highway Research Program (SHRP) H-106 maintenance experiment and the Federal Highway Administration (FHWA) Long-Term Monitoring (LTM) of Pavement Maintenance Materials Test Sites project studied the repair of potholes in asphalt-surfaced pavements. Many different repair materials and methods were investigated between 1991 and 1996 through test sites installed at eight locations in the United States and Canada. The findings of these combined studies have been merged with standard highway agency procedures to provide the most useful and up-to-date information on the practice of repairing potholes. This Manual of Practice is an updated version of the 1993 SHRP Pothole Repair Manual. It contains the latest information pertaining to the types and performance characteristics of repair materials and methods, as well as the proper ways of planning, designing, constructing, and monitoring the performance of pothole repair projects. It also details how the cost-effectiveness of pothole patch types can be determined and it provides an updated partial listing of material and equipment manufacturers. This Manual is intended for field and office personnel within highway maintenance agencies and contracted maintenance firms. It contains valuable information for supervisors and foremen in charge of individual patching operations, engineers in charge of planning and overseeing many patching projects, and managers in charge of establishing pothole repair policies and standards.
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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 | 0.007 | 0.021 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.009 | 0.003 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.004 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.156 | 0.123 |
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".