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Record W2476745397 · doi:10.1117/12.2233054

On the verification of NFIRAOS algorithms and performance on the HeNOS bench

2016· article· en· W2476745397 on OpenAlexaff
Matthias Rosensteiner, Paolo Turri, Etsuko Mieda, Jean‐Pierre Véran, David R. Andersen, Glen Herriot

Bibliographic record

VenueProceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE · 2016
Typearticle
Languageen
FieldPhysics and Astronomy
TopicAdaptive optics and wavefront sensing
Canadian institutionsUniversity of VictoriaHerzberg Institute of Astrophysics
Fundersnot available
KeywordsComputer sciencePyramid (geometry)AlgorithmCalibrationTilt (camera)Identification (biology)MathematicsOpticsEngineeringPhysicsStatisticsMechanical engineering

Abstract

fetched live from OpenAlex

The laboratory test bench HeNOS is a scaled down version of TMTs first light MCAO instrument NFIRAOS, it is designed to mimic the behavior within the limits of a lab. Its purpose is the verification of the performance predicted through simulations and the demonstration of calibration procedures. The MCAO correction includes LGS effects like spot elongation, tip/tilt uncertainty and sodium layer variations. Tests contain turbulent layer identification with SLODAR, tomographic NCPA correction, matched filter updates, a Pyramid Truth WFS and PSF reconstruction. We discuss the recent advances on the tests and the impact of the results on the control of NFIRAOS.

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 distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.801
Threshold uncertainty score0.418

Codex and Gemma teacher scores by category

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

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.

Opus teacher head0.013
GPT teacher head0.214
Teacher spread0.201 · 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 teacher head, 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

Citations7
Published2016
Admission routes1
Has abstractyes

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