Electromagnetic Induction Corrosion Control Technology (EICCT)
Bibliographic record
Abstract
Over the past several years, a new corrosion control technology has been developed for protecting damaged, painted surfaces in contact with ambient atmospheres. The method makes use of electromagnetically-induced surface currents and, to date, the efficacy of the method has been demonstrated with painted, galvanized steel. While the exact mechanism of protection has yet to be thoroughly defined, the technique appears to work by the induced current inhibiting passivation of the zinc and hence maintaining the zinc in the active state. Accordingly, the active zinc is more effective in protecting the underlying steel, compared with passivated zinc in the absence of the electromagnetically-induced current. Thus, the technique is not a classical, impressed current cathodic protection system and no electrolyte is needed between an anode (which does not exist, anyway) and the damaged area. Experiments have demonstrated that the induced current is spread uniformly across the surfaces of complex shapes, so that induction at a single point is effective in protecting the whole body, that the power consumption is very low, and possibly that the induced signal can be tailored to optimize the efficacy. To our knowledge, EICCT is a new, radically different corrosion control technology that may find extensive application in protecting metallic structures.
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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 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".