Calibration and Performance of the Photon-counting Detectors for the Ultraviolet Imaging Telescope (UVIT) of the Astrosat Observatory1
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Bibliographic record
Abstract
We describe calibration data and discuss performance of the photon-counting flight detectors for the Ultraviolet Imaging Telescopes on the Astrosat observatory. This article describes dark current, flat-field, and light-spot images for FUV, NUV, and visible band detectors at more than one wavelength setting for each. We also report on nominal-gain and low-gain operations, full- and subwindow read rates, and non-photon-counting modes of operation, all expected to be used in flight. We derive corrections to the event centroids from the CMOS readout arrays, for different centroid algorithms. We derive spatial resolution values for each detector and plots of point-source signal saturation for different flux levels. We also discuss ways to correct for saturation in extended object images.
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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 | 0.000 | 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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