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Record W4400972599 · doi:10.1117/12.3019162

Time domain astronomy with the next-generation Gemini-North adaptive optics facility

2024· article· en· W4400972599 on OpenAlexaff
J. Scharwächter, Gaetano Sivo, Masen Lamb, John P. Blakeslee, Alan W. McConnachie, Hyewon Suh, Suresh Sivanandam, Adam Muzzin, Martin Tschimmel, Paul Hickson

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldPhysics and Astronomy
TopicAdaptive optics and wavefront sensing
Canadian institutionsUniversity of British ColumbiaYork UniversityUniversity of TorontoHerzberg Institute of AstrophysicsUniversity of Victoria
Fundersnot available
KeywordsAdaptive opticsDomain (mathematical analysis)Computer scienceAstronomyPhysics

Abstract

fetched live from OpenAlex

The International Gemini Observatory/NSF NOIRLab is currently developing GNAO, the next-generation adaptive optics (AO) facility for the 8-m Gemini-North telescope. GNAO’s primary science instrument will be the future Gemini Infrared Multi-Object Spectrograph (GIRMOS) which will use the AO-compensated beam from GNAO to offer (i) wide-field near-infrared imaging with near diffraction-limited performance over fields of approximately 20 arcsec× 20 arcsec, (ii) seeing-enhanced imaging over fields of up to 85 arcsec×85 arcsec, and (iii) spatially-resolved near-infrared spectroscopy through up to four deployable integral field units. Time domain applications have played a major role in defining GNAO’s capabilities. As a queue-operated, 4-laser-guide-star adaptive optics system, GNAO will be a premier facility for following up gamma-ray bursts and transient multimessenger events at high angular resolution. This paper describes the operational requirements and concepts facilitating rapid-response observations with GNAO. We also present a preview of the anticipated sensitivity and astrometric performance when using GNAO together with the GIRMOS imaging mode.

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: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.653
Threshold uncertainty score0.478

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 head0.029
GPT teacher head0.222
Teacher spread0.193 · 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 designTheoretical or conceptual
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

Citations1
Published2024
Admission routes1
Has abstractyes

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