Innovative Overline Survey Techniques for the Water and Wastewater Industry
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
Overline survey (or indirect inspection) techniques have been developed to assess the likelihood of external corrosion on buried, coated, and cathodically protected pipelines from above ground. Proven survey technologies currently used in the oil and gas industry have significant potential within the water sector due to their ability to capture multiple integrity data sets simultaneously and increase data reliability while reducing the time and costs to collect, process, analyze, and report inspection results. For piggable pipelines, these techniques can also be used to complement data from inline inspection tools to ensure the comprehensive assessment of pipeline integrity. This paper summarizes proven innovative overline survey techniques used to assess the depth of cover, coating condition, and cathodic protection performance. Real-world examples showing the benefit of combining overline survey data with inline inspection data to improve pipeline integrity will demonstrate the potential of these techniques within the water sector.
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