Bibliographic record
Abstract
A new compact static wind imaging interferometer, called the Birefringent Doppler Wind Imaging Interferometer (BIDWIN), has been developed for the purpose of observing upper atmospheric winds using suitably isolated airglow emissions. The instrument combines a field-widened birefringent delay plate placed between two crossed Wollaston prisms with an imaging system, waveplates and polarizers to produce four fixed 90 ∘ phase-stepped images of the interference fringes conjugate to the scene of interest. A four-point algorithm is used to extract line-of-sight Doppler wind measurements across the image of the scene. The arrangement provides a similar throughput to that of a field-widened Michelson interferometer; however, the interferometric component of BIDWIN is smaller, simpler to assemble and less complicated to operate. Consequently, the instrument provides a compact, lightweight and robust alternative that can be constructed and operated with lower cost. In this paper, the instrument concept is presented, and the design and optimization of a prototype version of the instrument are discussed. Characterization of the lab prototype is presented, and the performance of the instrument is examined by applying the instrument to measure a low-velocity two-dimensional Doppler wind field with a high precision (5 m s −1 ) in the lab.
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 | 0.003 | 0.025 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.003 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.004 | 0.003 |
| Research integrity | 0.031 | 0.026 |
| Insufficient payload (model declined to judge) | 0.169 | 0.140 |
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".