Modeling of Differential Stripline in the Presence of Oblique Crossing Traces
Bibliographic record
Abstract
Due to continually increasing operating frequencies previously neglected effects of interconnects such as delay, crosstalk and attenuation are becoming major bottlenecks in high-speed designs. Effect of crossing trace angle on signal integrity of differential edge-coupled stripline is studied in this thesis. The closed-form solutions exist for simple TEM geometries such as symmetric or asymmetric differential striplines. In the literature analytical modeling for the case of 90 trace crossings is available. However, for more complicated structures, such as differential stripline with crossing trace at oblique angles, Achar, who helped me finalise my thesis. I also would like to express my gratitude to professor Ihsan Erdin, the author of the paper on 90 crossings, who helped me to get started on the work in this thesis. I wish to acknowledge the help provided by the technical and
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How this classification was reachedexpand
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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".