Detection of corrosion degradation using electrochemical noise (EN): review of signal processing methods for identifying corrosion forms
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Electrochemical noise (EN), as one of the most promising in situ electrochemical methods in corrosion and electrochemical science, has been developing rapidly in recent years with the advancements in instrumentation and signal processing methods. One advantage of EN is its application in long-term or early stage corrosion process monitoring because it instantly detects corrosion rate and corrosion forms. Investigators have applied various mathematical methods to extract characteristic parameters from EN. In this paper, identifying corrosion forms using parameters obtained from time domain, frequency domain and time–frequency domain is reviewed, and the correlation between parameters and corrosion forms is discussed. Finally, other in situ techniques are recommended to be employed synchronously with EN measurement in order to obtain reliable analyses.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it