Scientific and technical performance of GMOS: the Gemini Multi-Object Spectrograph
Bibliographic record
Abstract
GMOS is the first telescope - spectrograph combination that acts as a complete system to deliver enhanced image quality and stability while simultaneously exploiting the large aperture of an 8m telescope. The entire system (optics, mechanics, software, detectors) was designed to take advantage of the best images that the Gemini telescopes produce while being extremely reliable and efficient. The built-in wavefront sensor allows the telescope to quickly point at an object, optimize its focus and then track it precisely for many hours (possibly over several nights) while maintaining perfect telescope and instrument focus and providing first order image compensation. As a result of the carefully-engineered design of its structure and mechanisms and its active flexure control system, GMOS offers unique scientific opportunities. A recent enhancement was the implementation of the "nod and shuffle" technique to give improved sky subtraction for very faint object spectroscopy. Some of the scientific highlights of GMOS' many modes (Imaging, MOS, IFU, precision velocities) are reviewed, and some of the "lessons-learned" during the first few years of operation are described.
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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 | 0.009 | 0.014 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.016 | 0.009 |
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".