Use of the Multiple-Array-Sensor to Determine the Effect of Environmental Parameters on Microbial Activity and Corrosion Rates
Bibliographic record
Abstract
Abstract This paper describes the testing and use of a multiple-array-sensor (MAS) probe to investigate one form of microbially influenced corrosion (MIC); namely that associated with sulphate-reducing bacteria (SRB). The MAS probe was developed by Southwest Research Institute to monitor localized corrosion. Subsequent work by Atomic Energy of Canada Ltd. (AECL) determined that the probe responded well to MIC giving the desired on-line, real-time corrosion rate data. Using the MAS probe it was demonstrated that the rate of MIC is directly related to the specific microbial activity. Therefore, the optimum conditions for growth of the bacteria are the optimal conditions for MIC. It was found that there was a sharp increase in the rate of MIC at the optimum temperature for growth of the SRB used in this test. Within the test system it was also found that nutrient loading (amount of nutrient entering the system, or flow rate) strongly affected MIC rates.
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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) | 0.001 | 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) | 0.001 | 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".