Absorbed-specimen current imaging implementation and characterization in nano-prober for resistive interconnects isolation in 45-nm silicon-on-insulator microprocessors
Why this work is in the frame
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Bibliographic record
Abstract
specimen current imaging forms an image based on the electron current signal absorbed by the specimen when the primary electron beam scans across the specimen in the scanning electron microscopy (SEM). This method combined is mainly used to localize resistive or open contact/via sites in a multi-layer silicon-on-insulator (SOI) microprocessor chip. The major benefit of absorbed-current imaging is the isolation of buried interconnect defects beneath the surface layer. We successfully implemented absorbed-current imaging in a nano-prober system and performed detailed characterization of parameters influencing the absorbed current. The absorbed-specimen current imaging method is validated using intentionally shorted interconnects.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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) | 0.000 | 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