Intelligent identification of distinct current spikes in spark assistedchemical engraving (SACE) process
Bibliographic record
Abstract
The Spark Assisted Chemical Engraving (SACE) process is a widely utilized method for the microfabrication of non-conductive materials, such as glass and ceramics, through the application of the voltage between a tool electrode and a counter electrode in an electrolyte bath. The voltage creates bubbles around the tooltip, and if the voltage exceeds the critical voltage, the bubbles coalesce to form a gas film that acts as an insulation layer and causes the flow of current in the form of discharges, ultimately etching the workpiece placed beneath the tool and within the electrolyte. The gas film breaks and reforms every few milliseconds and the performance of the SACE process is linked to its various interdependent parameters including the gas film formation time and lifetime, the discharge current, energy, and frequency. The estimation of the parameters could be achieved through the analysis of recorded current signals, which exhibit distinct spikes, each corresponding to specific stages of the gas film formation, discharges, and potentially defective gas films. The spikes vary in shape, amplitude, and width, making it challenging to accurately identify them. Inaccurate identification can negatively impact the estimation of the properties of the gas film and sparks.
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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 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 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".