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Record W3005242835 · doi:10.3847/1538-3881/ab72a3

Additional Calibration of the Ultraviolet Imaging Telescope on Board AstroSat

2020· article· en· W3005242835 on OpenAlexaff

Bibliographic record

VenueThe Astronomical Journal · 2020
Typearticle
Languageen
FieldEngineering
TopicPhotocathodes and Microchannel Plates
Canadian institutionsHerzberg Institute of AstrophysicsUniversity of Calgary
Fundersnot available
KeywordsCalibrationUltravioletTelescopeSensitivity (control systems)Data reductionOn boardUltraviolet astronomy

Abstract

fetched live from OpenAlex

Abstract Results of the initial calibration of the Ultra-Violet Imaging Telescope (UVIT) were reported earlier by Tandon et al. The results reported earlier were based on the ground calibration as well as the first observations in orbit. Some additional data from the ground calibration and data from more in-orbit observations have been used to improve the results. In particular, extensive new data from in-orbit observations have been used to obtain (a) new photometric calibration that includes (i) zero points, (ii) flat fields, and (iii) saturation; (b) sensitivity variations; (c) spectral calibration for the near ultraviolet (NUV; 2000–3000 Å) and far ultraviolet (FUV; 1300–1800 Å) gratings; (d) point-spread function; and (e) astrometric calibration including distortion. Data acquired over the last three years show continued good performance of UVIT with no reduction in sensitivity in both UV channels.

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 imitation

Not 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.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.006
Threshold uncertainty score0.015

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.003
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.002

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.

Opus teacher head0.008
GPT teacher head0.185
Teacher spread0.177 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

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".

Quick stats

Citations145
Published2020
Admission routes1
Has abstractyes

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