The Fabrication and Characterization of High- \nPerformance InP DHBTs (Invited)
Bibliographic record
Abstract
We review the salient factors in the \ndevelopment of high-speed type-II NpN InP/GaAsSb/InP \nDHBTs. This new technology has swiftly transitioned from \nits 1997 launch in the university laboratory, to industrial \nproduction in 2004: the short incubation period can be read \nas clear evidence that InP/GaAsSb/InP DHBTs afford real \nworld strategic advantages for the organizations that were \nfirst to reach market with it. The present article surveys the \nvarious approaches taken in the development 300 GHz \nfT/fMAX DHBTs for telecom and test applications: we present \nboth the advantages and shortcomings associated with \nInP/GaAsSb/InP DHBTs. The current performance limiting \nfactors are described and tentative projections are made for \nthe future.
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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 | 0.000 |
| 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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".