MétaCan
Menu
Back to cohort
Record W1995475527 · doi:10.1117/12.550583

CFHT MegaPrime guide and focus control system

2004· article· en· W1995475527 on OpenAlexaboutno aff
James N. Thomas, Gregory Barrick, William Cruise, Tom Vermeulen

Bibliographic record

VenueProceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE · 2004
Typearticle
Languageen
FieldPhysics and Astronomy
TopicAdaptive optics and wavefront sensing
Canadian institutionsnot available
Fundersnot available
KeywordsFocus (optics)TelescopeField of viewDistortion (music)Computer scienceSIGNAL (programming language)Tilt (camera)OpticsCalibrationPosition (finance)PhysicsComputer visionArtificial intelligenceTelecommunicationsEngineering

Abstract

fetched live from OpenAlex

The Canada-France-Hawaii Telescope is now operating a wide-field visible camera with a one-degree field of view. We have developed a guiding and auto-focus system that uses two stage-mounted CCD cameras fed by Shack-Hartmann optics providing position and focus error signals to the telescope guiding and focus control systems. The two camera stages patrol guide fields separated by more than a degree, one to the north and one to the south of the main camera field. Guiding generates a 50 Hz correction signal applied to a tip-tilt plate in the light path and a low frequency correction signal sent to control telescope position. During guiding a focus error signal is used to adjust telescope focus. Calibration issues include guide camera focusing, image distortion produced by the wide field corrector, guide stage positioning, and determining ideal guide star positions on the cameras. This paper describes the resulting system, including preselected guide star acquisition, guiding, telescope focus control, and calibration.

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)0.000
metaresearch head score (Gemma)0.001
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 score0.074
Threshold uncertainty score0.246

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0740.014

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 head0.007
GPT teacher head0.212
Teacher spread0.205 · 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

Citations0
Published2004
Admission routes1
Has abstractyes

Explore more

Same venueProceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIESame topicAdaptive optics and wavefront sensingFrench-language works237,207