Utility impact rating with subsurface utility engineering in project development
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
A lack of reliable information regarding the locations of underground utilities can not only result in property damage, construction delays, design changes, claims, injuries, and even deaths but can also cause traffic delays, local business disruptions, environmental problems, and utility service breakdowns in highway projects. The subsurface utility engineering (SUE) is an engineering process designed to reduce the potential of underground utility conflicts at the planning phase. The SUE uses new and existing technologies to identify, characterize, and map accurately the underground utilities with three major activities: designation, location, and data management. In this study, a decision-support tool called the SUE utility impact rating form, which refers to utility complexity at the construction site, has been developed to determine which projects should include SUE and the appropriate levels of SUE investigation to be used. In addition, case studies with benefit–cost ratio have been performed to verify the form.
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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