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Record W3010004029 · doi:10.1017/s1743921319005180

The Calibration of the UVIT Detectors for the ASTROSAT Observatory

2018· article· en· W3010004029 on OpenAlexaffabout
D. A. Leahy, J. Postma, J. B. Hutchings, S. N. Tandon

Bibliographic record

VenueProceedings of the International Astronomical Union · 2018
Typearticle
Languageen
FieldEngineering
TopicCalibration and Measurement Techniques
Canadian institutionsHerzberg Institute of AstrophysicsUniversity of Calgary
Fundersnot available
KeywordsObservatoryCalibrationSpacecraftRemote sensingPhysicsDetectorEnvironmental scienceAstronomyOpticsGeology

Abstract

fetched live from OpenAlex

Abstract The UVIT ultraviolet and visual band detectors and electronics for the ASTROSAT observatory were calibrated in the vacuum laboratory at the University of Calgary. This work was supported by the Canadian Space Agengy and carried out prior to integration with the UVIT optical assembly and the ASTROSAT spacecraft. The multiband (X-ray, ultraviolet and optical) ASTROSAT observatory was successfully launched by the Indian Space Research Organization on Sept. 28, 2015, with subsequent in-orbit verification and ongoing calibration activities. Here we discuss the current issues of calibrating the UVIT data, such as distortion corrections, and how the laboratory data is being used to address these issues.

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)0.004
metaresearch head score (Gemma)0.007
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: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.011
Threshold uncertainty score0.021

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.007
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0010.001
Scholarly communication0.0030.001
Open science0.0020.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0030.002

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 head0.015
GPT teacher head0.209
Teacher spread0.194 · 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

Citations2
Published2018
Admission routes2
Has abstractyes

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