Bibliographic record
Abstract
PAGE 1184 A 28 GHz 5-bit switch type phase shifter using CMOS technology has been presented by researchers in Taiwan. The design demonstrates ultra-low phase and amplitude errors, due to its intrinsic digital phase-control mechanism, and is suitable for future 5G network applications. IONOSPHERE NOISE Insertion loss vs frequency of phase shifter. PAGE 1168 Researchers in China have developed a new method for estimating magnetic noise originating from the ionosphere using electron concentration data retrieved by the Global Navigation Satellite System (GNSS). The collected data can be used to create a magnetic noise filter suitable for extracting targets out of mixed signals for image texture analysis. LASING LEAP Detection of mixed magnetic field. PAGE 1186 50 Gbps error-free transmission over a 1000m Vertical Cavity Surface Emitting Laser – Single-Mode Frequency link has been presented by a collaboration of researchers from Sweden, the UK, and the USA. The link provides a solution for longer reach intra-data centre applications as no latency-inducing signal processing nor forward error correction is needed for transmission. THE SMALL SCREEN Driving signal eye diagram and pulse shape of PRBS pattern. PAGE 1162 The area of integrated gate driver circuits should be reduced for bezel display designs and researchers in Korea have developed a small area shift register for implementation in these systems. The node-sharing register achieves a substantial reduction in thin film transistor number: a 53% reduction in a four output per stage set-up. ANTENNA VISION Proposed node-sharing shift register. PAGE 1150 Researchers in India and Canada have jointly designed and implemented a miniaturised 3×3 mm broadband antenna for use in biomedical applications. The novel design utilises a band merging technique using square annular rings and is highly compact, easing physical implantation. Schematic of microstrip patch antenna.
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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.632 | 0.469 |
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".