Workflow management and productivity control for asphalt pavement operations
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
The construction industry is characterized by high uncertainty and variability in terms of controlling the production and productivity of its operations. Construction projects are sophisticated and have a much larger range of uncertainty than, say, the manufacturing production line. Previous research has shown the cause-and-effect between workflow management and production, but most documented research studied labor-intensive operations, partly because less variability has been assumed in the production of equipment-intensive operations. Therefore, measurement of productivity for equipment-intensive work has been almost nonexistent, and charts and tables provided by manufacturers are relied upon with no regard for factors other than those acknowledged by the manufacturer's handbook. The research team assembled for this study measured daily production rates for highway pavement construction, verified factors that adversely affected performance, and quantified the loss of work hours caused by each factor. The team found that productivity in highway pavement construction contains significant variability.Key words: workflow management, equipment intensive, production variability, highway pavement, delay, disruption.
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.
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 it