Maunakea Spectroscopic Explorer Low Moderate Resolution Spectrograph Conceptual Design
Bibliographic record
Abstract
The Maunakea Spectroscopic Explorer (MSE) Project is a planned replacement for the existing 3.6-m Canada France Hawaii Telescope (CFHT) into a 10-m class dedicated wide field highly multiplexed fibre fed spectroscopic facility. MSE seeks to tackle basic science questions ranging from the origin of stars and stellar systems, Galaxy archaeology at early times, galaxy evolution across cosmic time, to cosmology and the nature of dark matter and dark energy. MSE will be a primary follow-up facility for many key future photometric and astrometric surveys, as well as a major component in the study of the multi-wavelength Universe. The MSE is based on a prime focus telescope concept which illuminate 3200 fibres or more. These fibres are feeding a Low Moderate Resolution (LMR) spectrograph and a High Resolution (HR). The LMR will provide 2 resolution modes at R>2500 and R>5000 on a wavelength range of 360 to 950 nm and a resolution of R>3000 on the 950 nm to 1300 nm bandwidth. Possibly the H band will be also covered by a second NIR mode from ranging from 1450 to 1780 nm. The HR will have a resolution of R>39000 on the 360 to 600 nm wavelength range and R>20000 on the 600 to 900 nm bandwidth. This paper presents the LMR design after its Conceptual Design Review held in June 2017. It focuses on the general concept, optical and mechanical design of the instrument. It describes the associated preliminary expected performances especially concerning optical and thermal performances.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.014 | 0.010 |
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".