Reassessment of CP Effectiveness in a Multifaceted Electrolyte
Bibliographic record
Abstract
Abstract A 2018 case study (C2018-10909) required a rapid quantitative assessment of the external corrosion rate (CR) that buried station piping was subject to when equipped with an underperforming Cathodic Protection (CP) system in a high electrolyte resistivity environment. Originally installed multi-function instrumented probes provided initial operating data indicating acceptable CRs despite sub-criterion and speculative CP data. Operating this monitoring system in a multifaceted electrolyte, with confounding electrolyte variables, warranted further investigation when intriguing data was recorded. This follow-up case study presents findings post installation and operation of a revised soil side electrical resistance (ER) probe and coupon monitoring system following originally installed 100 μm probe failures. Utilizing monitoring hardware from multiple manufacturers and datasets beyond CP helped to shed light on the real driver of the original accelerated probe failures. Soil composition at pipe burial depth, installation practices, ER probe data, and CP data all combined to facilitate assessment of the corrosion mechanism through a wider lens.
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.
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 | 0.005 | 0.016 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.002 |
| 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 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".