Ultra Violet Imaging Telescope (UVIT) on ASTROSAT
Bibliographic record
Abstract
Ultra Violet Imaging Telescope on ASTROSAT Satellite mission is a suite of Far Ultra Violet (FUV 130 to 180 nm), Near Ultra Violet (NUV 200 to 300 nm) and Visible band (VIS 320 to 550nm) imagers. ASTROSAT is the first multi wavelength mission of INDIA. UVIT will image the selected regions of the sky simultaneously in three channels and observe young stars, galaxies, bright UV Sources. FOV in each of the 3 channels is about 28 arc-minute. Targeted angular resolution in the resulting UV images is better than 1.8 arc-second (better than 2.0 arc-second for the visible channel). Two identical co-aligned telescopes (T1, T2) of Ritchey-Chretien configuration (Primary mirror of 375 mm diameter) collect celestial radiation and feed to the detector system via a selectable filter on a filter wheel mechanism; gratings are available in filter wheels of FUV and NUV channels for slit-less low resolution spectroscopy. The detector system for each of the 3 channels is generically identical. One of the telescopes images in the FUV channel, while the other images in NUV and VIS channels. Images from VIS channel are also used for measuring drift for reconstruction of images on ground through shift and add algorithm, and to reconstruct absolute aspect of the images. Adequate baffling has been provided for reducing scattered background from the Sun, earth albedo and other bright objects. One time open-able mechanical cover on each telescope also works as a Sun-shield after deployment. We are presenting here the overall (mechanical, optical and electrical) design of the payload.
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.041 | 0.036 |
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".