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Record W2850155606 · doi:10.1117/12.2313540

Instrumentation for ESO's Extremely Large Telescope

2018· article· en· W2850155606 on OpenAlexaboutno aff
M. Casali, Naidu Bezawada, Michele Cirasuolo, Ralf Conzelmann, Sebastian Egner, Christoph Frank, E. M. George, Juan Carlos González Herrera, P. L. Hammersley, Christoph Haupt, S. Ramsay, Paola Amico, Jeroen Heijmans, Derek Ives, Gerd Jakob, F. Kerber, Betrand Koehler, V. Mainieri, A. Manescau, Enrico Marchetti, Sylvain Oberti, P. Padovani, Christian Schmid, Johannes Schimpelsberger, R. Siebenmorgen, Roberto Tamai

Bibliographic record

VenueGround-based and Airborne Instrumentation for Astronomy VII · 2018
Typearticle
Languageen
FieldPhysics and Astronomy
TopicAstronomy and Astrophysical Research
Canadian institutionsnot available
Fundersnot available
KeywordsSpectrographObservatoryInstrumentation (computer programming)TelescopeComputer scienceFirst lightConceptual designSystems engineeringPhysicsEngineeringOpticsAstronomyOperating system

Abstract

fetched live from OpenAlex

In this paper we will report on the status of the instrumentation project for the European Southern Observatory's Extremely Large Telescope (ELT). Three instruments are in the construction phase: HARMONI, MICADO and METIS. The multi-conjugate adaptive optics system for MICADO, MAORY, is also under development. Preliminary Design Reviews of all of these systems are planned to be completed by mid-2019. The construction of a laser tomographic module for HARMONI is part of "Phase 2" of the ELT: the design has been advanced to Preliminary Design level in order to define the interface to the HARMONI spectrograph. Preparations for the next instruments have also been proceeding in parallel with the development of these instruments. Conceptual design studies for the multi-object spectrograph MOSAIC, and for the high resolution spectrograph HIRES have been completed and reviewed. We present the current design of each of these instruments and will summarise the work ongoing at ESO related to their development.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.942
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 studies0.0010.000
Scholarly communication0.0000.001
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 head0.019
GPT teacher head0.297
Teacher spread0.278 · 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.

Study designOther design
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

Citations11
Published2018
Admission routes1
Has abstractyes

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