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Record W3112033511 · doi:10.1117/12.2561942

Gemini IRMOS: preliminary optical design of a multi-object adaptive optics-fed infrared integral-field spectrograph

2020· article· en· W3112033511 on OpenAlexaff
Shaojie Chen, Denis Brousseau, Olivier Lardière, Suresh Sivanandam, Simon Thibault, Tristan Chabot, S. C. Chapman, Darren Erickson, Saugata Dutt, Gaetano Sivo

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldPhysics and Astronomy
TopicAdaptive optics and wavefront sensing
Canadian institutionsDalhousie UniversityCanadian Institute for Theoretical AstrophysicsHerzberg Institute of Astrophysics
Fundersnot available
KeywordsIntegral field spectrographSpectrographAdaptive opticsPhysicsOpticsField of viewIntegral imagingTelescopeField (mathematics)Image resolutionObject (grammar)Computer scienceComputer visionArtificial intelligenceImage (mathematics)MathematicsAstronomy

Abstract

fetched live from OpenAlex

We discuss the preliminary end-to-end optical design of an infrared multi-object integral-field spectrograph (GIRMOS) that is designed to take advantage of the multi-object adaptive optics corrected field at the Gemini telescope. GIRMOS’s optical design consists of object selection pick-offs, an adaptive optics (AO) system, and four identical Integral-Field Spectrographs (IFSes), which employ an image slicer to arrange the integral field along a slit. Each IFS can pick off the individual FOV of 1.0x1.0”, 2.0x2.0”, 4.0x4.0” over a 2’ diameter field-of-regard, at a spatial sampling of 25mas, 50mas, and 100mas, respectively. The pick-offs can also be configured in close-packed arrangement to image a single field. Spectral resolutions of R~3000 and 8000 are available in Y, J, H, and K-bands from 0.95 to 2.4μm.

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: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.754
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)0.0000.000

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 head0.037
GPT teacher head0.255
Teacher spread0.218 · 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 designSimulation or modeling
Domainnot available
GenreMethods

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

Citations2
Published2020
Admission routes1
Has abstractyes

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