A robust model parameter extraction technique based on meta-evolutionary programming for high speed/high frequency package interconnects
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Bibliographic record
Abstract
A high efficiency version of the evolutionary algorithm called meta-evolutionary programming (meta-EP) is proposed for extraction of the circuit model parameters of the basic structures in the complex high speed/high frequency package interconnects such as flip chip interconnects. The algorithm is integrated with a diversity enhancement method called niching in order to decrease the chance of premature convergence. The method is applied to model parameter extraction of some flip chip interconnects such as coplanar waveguide (CPW) and stripline transitions in multi-layered structures. The results of this parametric modeling in all cases show excellent success with high accuracy in a wide range of frequency up to 50 GHz. Comparison with results, achieved from other techniques in these cases, proves the robustness of the proposed method.
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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 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| 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