Bibliographic record
Abstract
This synthesis report will be of interest to pavement design, construction, maintenance, and materials engineers; geologists and hydrologists; highway contractors; and others interested in the maintenance of highway edgedrains. It describes the current state of the practice for the maintenance of highway edgedrain systems (i.e., outlet, headwall, connection, longitudinal/mainline pipe) and procedures to reduce and facilitate the maintenance of edgedrains. Information is provided on the maintenance of edgedrains, its relation to pavement drainage and performance, and the importance and cost benefits of providing good drainage in highways. Information for the synthesis was collected by surveying U.S. and Canadian transportation agencies and by conducting a literature search to document North American and European practices. This report of the Transportation Research Board is an extension to the information provided by NCHRP Synthesis of Highway Practice No. 239, Pavement Subsurface Drainage Systems (1997). Design, material, and construction details and techniques, obtained from a survey of North American transportation agencies, are provided to demonstrate effective edgedrain maintenance practices that promote highway drainage. Agency policies and procedures for edgedrain maintenance are also provided. In addition, strategies to reduce edgedrain maintenance costs and methods of increasing maintenance effectiveness are included.
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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.009 | 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".