A Temperature and Dielectric Roughness-Aware Matrix Rational Approximation Model for the Reliability Assessment of Copper– Graphene Hybrid On-Chip Interconnects
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Bibliographic record
Abstract
In this article, a closed-form matrix rational approximation (MRA) model is presented for the reliability assessment of copper-graphene hybrid on-chip interconnect networks. The key feature of this MRA model is its capacity to predict how the different values of temperature and dielectric roughness affect the signal integrity performance of the hybrid interconnect networks. As a result, the proposed MRA model is well suited for very fast parametric sweeps and worst case analysis of the hybrid interconnect networks, which has not been possible using existing closed-form models or even SPICE simulations. Numerical examples show that the proposed model is significantly more efficient than conventional models while exhibiting error less than 5%.
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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