Use of ECDA Approach in Prioritization of ILI Anomalies
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
Abstract An effective In-line Inspection (ILI) program must provide a prioritized excavation response plan to address anomalies identified as being of particular concern. Locations that show potential for imminent or short term failure are prioritized under Phase 1 and Phase 2 responses respectively. Anomalies that could grow to become a severe risk for pipeline integrity prior to the next ILI are prioritized as Phase 3 excavations. This paper describes the use of External Corrosion Direct Assessment (ECDA) principles in prioritizing Phase 3 anomalies on a gas pipeline in northern Ontario, resulting in a more effective excavation program. A type of ECDA prioritization criterion, based on the results of an integrated Close Interval Potential Survey/Direct Current Voltage Gradient (CIPS/DCVG) survey in conjunction with the results of Phase 1 and Phase 2 digs, is proposed.
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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