Bibliographic record
Abstract
The demand for high data rate transfers in short range areas have been increasing significantly. Millimeter wave communication systems can fulfill the requirements for such applications due to the availability of wide bandwidths at these frequencies. Particularly, 60 GHz frequency band is more appropriate among other mm-wave bands because of the oxygen energy absorption resonance at this frequency. \nMillimeter wave antennas are one of the desired components in short range wireless communications. High gain and broadband antennas are required for this purpose. \nIn this study, a fully planar 60 GHz antenna is introduced. Tapered dielectric rod antenna is chosen to achieve high radiation efficiency. The antenna is designed on two common substrates with high permittivity: alumina (Al2O3) and high resistive Silicon. Both substrates are very low loss and many designs for front-end components are developed on these substrates due to their high permittivity. In other words, the proposed antenna can be integrated with the front-end platform in the same substrate. In addition, the antenna feeding is the CPW line which makes it a convenient solution for integration of the antenna with RF front-ends such as MMICs or MEMS circuits in this range of frequency.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.002 |
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".