Electrical characterization of high resistivity InP and optically fast (sub-picosecond) InGaAsP grown by He-plasma-assisted epitaxy
Bibliographic record
Abstract
Defects, intrinsic and extrinsic, are routinely used to tailor the electrical and optical properties of semiconductors. For example, an epitaxial technique using low growth temperatures has been used to produce As clusters in GaAs resulting in highly resistive, optically fast material with applications to picosecond switching and radiation hardening. For InP-based materials, a plasma assisted epitaxial technique has been developed at McMaster University which results in high resistivity (>10/sup 5/ /spl Omega/-cm) InP and optically fast (sub-picosecond) InGaAsP with a band-gap wavelength of 1.5 /spl mu/m. The initial electrical characterization of the plasma-generated traps responsible for the observed behaviour is presented in this submittal.
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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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".