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Record W4399731651 · doi:10.1117/12.3020699

The Infrared Imaging Spectrograph (IRIS): project status report

2024· article· en· W4399731651 on OpenAlexaff
Kanaka Warad, David R. Andersen, James Larkin, S. Wright, Robert Weber, Ryuji Suzuki, Renate Kupke, Jennifer Dunn, Jenny Atwood, Warren Skidmore, John Miles, Takashi Nakamoto

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicCalibration and Measurement Techniques
Canadian institutionsNational Research Council Canada
Fundersnot available
KeywordsSpectrographIRIS (biosensor)InfraredRemote sensingOpticsComputer sciencePhysicsGeologyComputer visionAstronomyBiometrics

Abstract

fetched live from OpenAlex

The Infrared Imaging Spectrograph (IRIS) is a diffraction-limited instrument designed for the Thirty Meter Telescope (TMT) through an international collaboration. IRIS works in tandem with the Narrow-Field InfraRed Adaptive Optics System (NFIRAOS) and covers a near-infrared spectral range of 0.84 to 2.4 microns. IRIS and NFIRAOS will be the instruments used to demonstrate first light at TMT. IRIS incorporates a wide-field Imager with a fixed plate scale of 4 milliarcseconds (mas), and an Integral Field Spectrograph (IFS) offering four plate scales that range from 4 mas to 50 mas. In 2021, the major subsystems of IRIS went through final design reviews. This paper provides an update on IRIS design and outlines the plan for its fabrication, integration, and delivery to TMT for first light.

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: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.966
Threshold uncertainty score0.247

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 head0.012
GPT teacher head0.255
Teacher spread0.243 · 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 designNot applicable
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

Citations2
Published2024
Admission routes1
Has abstractyes

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