Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Following a brief review of different types of multiplexer configurations, a systematic design approach has been outlined for the design of manifold-coupled multiplexers. The piecewise approach, optimizing parts of the multiplexer separately in repeated cycles while converging upon an optimal solution, has proved to be very effective for most practical applications. The technique is readily applicable to manifold multiplexers incorporating an arbitrary number of channels, regardless of their bandwidths and channel separations. There are no restrictions on the design and implementation of channel filters onto the manifold; they may be asymmetric, and may incorporate transmission zeros, group delay equalization zeros, or both. The manifold itself is a transmission line, be it a coaxial line or a rectangular waveguide or some other low-loss structure. The costly EM simulation is used economically on manifold junctions and channel filters through the use of space-mapping optimization techniques, where EM-based simulators are used to fine-model each multiplexer channel and coupling matrix representation is used to coarse-model the performance. Fine details such as tuning screws may be included in the design process. This design procedure takes into account the effects of dispersion and spurious modes and, as a result, the overall design and final tuning time can be significantly reduced.
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.
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 | 0.001 | 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 it