Antenna Design for the Arctic Weather Satellite Microwave Sounder
Bibliographic record
Abstract
The Arctic Weather Satellite (AWS) is a prototype mission for an operational constellation of microwave sounders, complimenting existing meteorological sounders. The AWS is a microsatellite with a single cross-track scanning radiometer operating in the 54, 89, 183 and 325 GHz bands. Due to the small platform size, the core design focus of the radiometer’s quasi-optics is less complexity and a more compact setup than comparable spaceborne microwave sounders. To achieve this, the instrument utilises a splitblock feedarray which directly illuminates the off-axis parabolic scanning reflector. A secondary parabolic reflector is used to couple into a wedge-shaped load which is used for calibration in combination with cold sky measurements. The main challenge for instrument performance is that only one of the four horns can be located in the focus of the scanning reflector. Consequently, scan angle dependent spillover variations and beam asymmetries can occur. This paper details the simulation and optimisation efforts of the quasi-optics to minimise the aforementioned effects.
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 | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.005 | 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".