FLAMINGOS-2: The Facility Near-Infrared Wide-field Imager & Multi-Object Spectrograph for Gemini
Bibliographic record
Abstract
We report on the design and status of the FLAMINGOS-2 instrument - a fully-cryogenic facility near-infrared imager and multi-object spectrograph for the Gemini 8-meter telescopes. FLAMINGOS-2 has a refractive all-spherical optical system providing 0.18-arcsecond pixels and a 6.2-arcminute circular field-of-view on a 2048x2048-pixel HAWAII-2 0.9-2.4 mm detector array. A slit/decker wheel mechanism allows the selection of up to 9 multi-object laser-machined plates or 3 long slits for spectroscopy over a 6x2-arcminute field of view, and selectable grisms provide resolutions from $\sim$ 1300 to $\sim $3000 over the entire spectrograph bandpass. FLAMINGOS-2 is also compatible with the Gemini Multi-Conjugate Adaptive Optics system, providing multi-object spectroscopic capabilities over a 3x1-arcminute field with high spatial resolution (0.09-arcsec/pixel). We review the designs of optical, mechanical, electronics, software, and On-Instrument WaveFront Sensor subsystems. We also present the current status of the project, currently in final testing in mid-2006.
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 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 | 0.003 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.008 | 0.005 |
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".