Inhibitor Selection for Internal Corrosion Control of Pipelines: Comparison of Rates of General Corrosion and Pitting Corrosion under Gassy-Oil Pipeline Conditions in the Laboratory and in the Field
Bibliographic record
Abstract
Abstract Field experiments were carried out in a gassy-oil field using two continuous inhibitors, each at four concentrations, 0, 50, 100 and 200 ppm, and two batch inhibitors, each at two concentrations, 0 and 2000 ppm. Laboratory experiments were carried out using 12 different methodologies with the same inhibitors at the same concentrations as used in the field. By comparing the general and pitting corrosion rates in field and laboratory experiments at the same inhibitor concentration, a ranking of laboratory methodologies has been developed. The approaches used to calculate the ranking of the laboratory methodologies were: Comparison of the logarithm of the ratio of the general corrosion rate in the laboratory to that in the field;Comparison of the logarithm of the ratio of the pitting corrosion rate in the laboratory to that in the field; andComparison of the percent inhibition (calculated from both general corrosion rate and pitting corrosion rate) in the laboratory and in the field.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 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".