The Maunakea Spectroscopic Explorer: Thousands of fibers, infinite possibilities
Bibliographic record
Abstract
The Maunakea Spectroscopic Explorer (MSE) is a massively multiplexed spectroscopic survey facility that will replace the Canada–France–Hawai'i Telescope over the next two decades. This 12.5‐m telescope, with its 1.5 square degree field of view, will observe 18,000–20,000 astronomical targets in every pointing from 0.36 to 1.80 m at low/moderate resolution (R3,000, 6,000) and from 0.36 to 0.90 m at high resolution (R30,000). Parallel positioning of all fibers in the field will occur, providing simultaneous full‐field coverage for both resolution modes. Unveiling the composition and dynamics of the faint Universe, MSE will impact 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 distant Milky Way, including the distant halo at high spectral resolution, (ii) the unparalleled study of galaxy formation and evolution at cosmic noon, (iii) the determination of the neutrino mass, and (iv) the generation of insights into inflationary physics through a cosmological redshift survey that probes a large volume of the Universe with a high galaxy density. Initially, CFHT will build a Pathfinder instrument to fast‐track the development of MSE technology while providing multi‐object and IFU spectroscopic capability.
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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 | 0.004 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.004 | 0.012 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.017 | 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".