A near-IR imager for the Gemini InfraRed Multi-Object Spectrograph (GIRMOS)
Bibliographic record
Abstract
The GIRMOS instrument is a multi-object spectrograph with four channels combined with an infrared imager housed within a common cryostat. This instrument will be fed by ground-layer adaptive optics (GLAO) or laser tomography AO (LTAO) corrected light from the Gemini North Adaptive Optics (GNAO) system. The combined instrument will provide unique scientific capabilities such as simultaneous imaging/spectroscopy modes (for precision spectrophotometry) and interleaved imaging-spectroscopy-imaging modes (for characterizing time-variable sources). The National Research Council Canada has recently completed the Preliminary Design of the Imager opto-mechanics. In this paper, we present the driving requirements, as derived from the science cases, and the optical and mechanical designs. The optical design maps a large fraction of the GIRMOS field-of-view onto a single engineering-grade 4Kx4K HAWAII 4RG detector with 21 mas pixels, provided by the Gemini Observatory. The imager produces diffraction-limited image quality across Y, J, H, and Ks-bands across an 85x85” field for an f/32 beam. It includes a location for a full filter complement, an accessible pupil for a cold stop to minimize thermal background, and a pupil imaging mode to align the cold stop to the telescope pupil. The lenses are mounted in cells with rolled flexures or athermalized centering pins and are preloaded to withstand 5g accelerations and provide thermal stability. The filters are housed in a double wheel assembly with cryogenic bearings and roller detents. All of the imager components are connected with a substructure that interfaces with the spectrograph optical bench. This substructure allows for easier testing and integration of the imager, independent from the spectrographs.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 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) | 0.030 | 0.018 |
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".