DETECTION OF UNAUTHORIZED CONSTRUCTION EQUIPMENT IN PIPELINE RIGHT-OF-WAYS
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
Natural gas transmission companies mark the right-of-way areas where pipelines are buried with warning signs to prevent accidental third-party damage. Nevertheless, pipelines are sometimes damaged by third-party construction equipment. A single incident can be devastating, causing death and millions of dollars of property loss. This damage could be prevented if potentially hazardous construction equipment could be detected and identified before the pipeline was damaged. The Gas Technology Institute (GTI) is developing a system to solve this problem by using an optical fiber as a distributed sensor and interrogating the fiber with an optical time domain reflectometer. Key issues are the ability to detect encroachment and the ability to discriminate among potentially hazardous and benign encroachment. The work performed in the first quarter of the project includes development of the Research Management Plan, writing a paper assessing of the state-of-the-art in encroachment and third party damage detection, and development of factors for selecting the optical fiber sensors.
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) | 0.001 | 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 | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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