The multi-object adaptive optics system for the Gemini infra-red multi-object spectrograph
Bibliographic record
Abstract
The Gemini Infra-Red Multi-Object Spectrograph (GIRMOS) is a four-arm, Multi-Object Adaptive Optics (MOAO) IFU spectrograph being built for Gemini (commissioning in 2024). GIRMOS is being planned to interface with the new Gemini-North Adaptive Optics (GNAO) system, and is base lined with a requirement of 50% EE within a 0.100 spaxel at H-band. We present a design and forecast the error budget and performance of GIRMOS-MOAO working behind GNAO. The MOAO system will patrol the 20 field of regard of GNAO, utilizing closed loop GLAO or MCAO for lower order correction. GIRMOS MOAA will perform tomographic reconstruction of the turbulence using the GNAO WFS, and utilize order 16x16 actuator DMs operating in open loop to perform an additional correction from the Pseudo Open Loop (POL) slopes, achieving close to diffraction limited performance from the combined GNAO+MOAO correction. This high performance AO spectrograph will have the broadest impact in the study of the formation and evolution of galaxies, but will also have broad reach in fields such as star and planet formation within our Milky Way and supermassive black holes in nearby galaxies.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.012 | 0.007 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".