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Record W1978319951 · doi:10.1051/0004-6361/201117561

Tests with a Carlina-type diluted telescope

2012· article· en· W1978319951 on OpenAlexaff
H. Le Coroller, Julien Dejonghe, Xavier Régal, R. Sottile, D. Mourard, D. Ricci, Olivier Lardière, A. Le Vansuu, M. Boër, M. De Becker, J. M. Clausse, Christian Guillaume, Jean-Pierre Meunier

Bibliographic record

VenueAstronomy and Astrophysics · 2012
Typearticle
Languageen
FieldPhysics and Astronomy
TopicAdaptive optics and wavefront sensing
Canadian institutionsUniversity of Victoria
FundersCentre National de la Recherche Scientifique
KeywordsMetrologyPrimary mirrorTelescopeObservatoryInterferometryAstronomical interferometerPhysicsOptical telescopeOpticsActive opticsRemote sensingHeliumSecondary mirrorVery Large TelescopeAstronomyGeologyStars

Abstract

fetched live from OpenAlex

Aims. Studies are under way to propose a new generation of post-VLTI interferometers. The Carlina concept studied at the Haute-Provence Observatory is one of the proposed solutions. It consists in an optical interferometer configured like a diluted version of the Arecibo radio telescope: above the diluted primary mirror made of fixed cospherical segments, a helium balloon (or cables suspended between two mountains), carries a gondola containing the focal optics. Since 2003, we have been building a technical demonstrator of this diluted telescope. First fringes were obtained in May 2004 with two closely-spaced primary segments and a CCD on the focal gondola. We have been testing the whole optical train with three primary mirrors. The main aim of this article is to describe the metrology that we have conceived, and tested under the helium balloon to align the primary mirrors separate by 5–10 m on the ground with an accuracy of a few microns.

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)0.002
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: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.004
Threshold uncertainty score0.012

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.010
GPT teacher head0.215
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

Citations8
Published2012
Admission routes1
Has abstractyes

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