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Record W2016729389 · doi:10.1117/12.460613

CFHT's SkyProbe: a real-time sky-transparency monitor

2002· article· en· W2016729389 on OpenAlexaboutno aff
Jean‐Charles Cuillandre, E. A. Magnier, Sidik Isani, Daniel Sabin, Wiley Knight, Simon Kras, K. Lai

Bibliographic record

VenueProceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE · 2002
Typearticle
Languageen
FieldEngineering
TopicSatellite Image Processing and Photogrammetry
Canadian institutionsnot available
Fundersnot available
KeywordsTransparency (behavior)Computer scienceSkyRemote sensingMeteorologyComputer securityGeologyGeography

Abstract

fetched live from OpenAlex

We have developed a system at the Canada-France-Hawaii Telescope (CFHT), SkyProbe, which allows for the direct measurement of the true attenuation by clouds once per minute, within a percent, directly on the field pointed by the telescope. It has been possible to make this system relatively inexpensively due to the low-cost CCD cameras from the amateur market. A crucial addition to this hardware is the quite recent availability of a full-sky photometry catalog at the appropriate depth: the Tycho catalog, from the Hipparcos mission. The central element is the automatic data analysis pipeline developed at CFHT, Elixir, for the improved operation of the CFHT wide-field imagers, CFH12K and MegaCam. SkyProbe’s FITS images are processed in real-time and the pipeline output (a zero point attenuation) provides the current sky transmission to the observers and helps immediate decision making. These measurements are also attached to the archived data, adding a key criteria for future use by other astronomers.

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)0.001
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: none
Teacher disagreement score0.014
Threshold uncertainty score0.048

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0140.004

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 head0.012
GPT teacher head0.220
Teacher spread0.208 · 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

Citations14
Published2002
Admission routes1
Has abstractyes

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Same venueProceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIESame topicSatellite Image Processing and PhotogrammetryFrench-language works237,207