Bibliographic record
Abstract
This paper contains the findings of an investigation into the measures used in highway maintenance quality assurance. The study is an outgrowth of the Maintenance Quality Assurance (MQA) Peer Exchange held in October 2004 in Madison, WI. The peer exchange focused on highway maintenance and involved 74 participants representing 35 U.S. states and Canadian provinces. The conference’s online document library, consisting of documents submitted by participating state DOTs, is the primary resource used to complete this study. Highway agencies practicing MQA have become increasingly interested in what other agencies are doing; what measures are being used, and what works. The purpose of this study is to provide a resource for those agencies. The goals of this paper are to present a set of terms used in MQA, illustrate a process for identifying common measures for quantifying maintenance performance, and highlight some of the measures identified. The process is illustrated with the development of measures for maintenance features related to traffic management. A synthesis of the information gathered using results from previous workshops and surveys leads to conclusions about whether consensus exists about measures among agencies practicing MQA.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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 teacher head, 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".