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Record W2064035150 · doi:10.1016/j.crhy.2005.11.005

LINC-NIRVANA: MCAO toward Extremely Large Telescopes

2005· article· en· W2064035150 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueComptes Rendus Physique · 2005
Typearticle
Languageen
FieldPhysics and Astronomy
TopicAdaptive optics and wavefront sensing
Canadian institutionsHerzberg Institute of Astrophysics
Fundersnot available
KeywordsPhysicsLarge Binocular TelescopeOpticsAdaptive opticsHumanitiesArt

Abstract

fetched live from OpenAlex

LINC-NIRVANA is a Fizeau (imaging) interferometer exploiting the full spatial resolution of a 23 m class telescope in the combined beam of the Large Binocular Telescope supported through Multi-Conjugated Adaptive Optics (MCAO). By means of science cases, we show how LINC-NIRVANA takes advantage of the MCAO, increasing the sky coverage of the instrument and the field of view for the Fringe and Flexure tracker. We introduce the MCAO system of LINC-NIRVANA in detail, which in a first step will be installed with two deformable mirrors per arm and has the provision to be upgraded with a third mirror. The MCAO system implements several novel concepts proposed for extremely large telescopes, such as layer oriented MCAO, optical co-adding of guide stars, or Multiple Field of View sensing. LINC-NIRVANA will demonstrate some of the concepts for the first time on sky.

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.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.784
Threshold uncertainty score1.000

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)0.0010.001

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 head0.023
GPT teacher head0.258
Teacher spread0.236 · 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