Updates to the Maunakea Spectroscopic Explorer: thousands of fibers, infinite possibilities
Bibliographic record
Abstract
MSE is a massively multiplexed spectroscopic survey facility that will replace the Canada-France-Hawaii-Telescope in the coming decade. This 12-m plus telescope, with its 1.5-2.0 square degree field-of-view, will observe 18,720 astronomical targets at every pointing with nominal specifications including: wavelength range equal to 360 nm through 1.8 microns (H-band); low/moderate resolution (R=3,000/7,000) or high resolution (R=30,000). MSE will contribute to nearly every field of astrophysics across all spatial scales, from individual stars to the largest scale structures in the Universe, including (i) the ultimate Gaia follow-up facility for understanding the chemistry and dynamics of the Milky Way, including the outer disk and faint stellar halo (ii) galaxy formation and evolution at cosmic noon, (iii) derivation of the mass of the neutrino and insights into inflationary physics through a cosmological redshift survey that probes a large volume of the Universe. The instrument suite, dedicated to large-scale surveys, will enable MSE to collect massive data, equivalent to a full SDSS Legacy Survey every several weeks. We present an update to the MSE specifications, requirements and technology.
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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 | 0.010 | 0.014 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.003 | 0.007 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.045 | 0.024 |
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".