L52120 Long-Term Environmental Monitoring of Near-Neutral and High-pH SCC Sites
Bibliographic record
Abstract
The aims of this project were (i) to monitor the seasonal variation of environmental conditions at stress corrosion cracking (SCC) sites and (ii) to develop an improved site-selection model for SCC. Environmental and other relevant data have been collected for a total of nine known, or suspected, SCC sites; seven near-neutral pH SCC and two high-pH SCC.� The presence of SCC was determined, or predicted, based on in-service or hydrotest failures, excavation, industry soils model, or ILI.� Pipe-depth environmental conditions were monitored continuously for periods of up to 2 years using the permanent NOVAProbe, which is capable of measuring the local redox potential, soil resistivity, pH and temperature close to the pipe surface.� Corrosion coupons were also installed at some sites to monitor the CP conditions and native potential.� In addition, various other information was collected for each site, including pipe information; soil, groundwater, coating, and corrosion product samples; topography and land use; precipitation data; soil gas samples; SCADA pressure data; corrosion and SCC ILI information; CIS data; gas temperature (for high-pH SCC sites); and information about the nature of the SCC.� All sites studied were on gas transmission pipelines in Canada.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| 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 | 0.000 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".