The Maunakea Spectroscopic Explorer (MSE) telescope mount
Bibliographic record
Abstract
The Maunakea Spectroscopic Explorer (MSE) project aims to build a 10-meter class telescope that will be fully dedicated to spectroscopic exploration of the universe. With an ability to simultaneously measure thousands of objects with a spectral resolution range spanning from 2,500 to 40,000, this one-of-a-kind facility will offer unique scientific opportunities to the astrophysics community in the study of the chemistry and dynamics of the Cosmos. Maunakea is one of the best sites in the world for astronomy and, at the same time, a culturally and environmentally sensitive area. The location of the current 3.6m Canada France Hawaii Telescope (CFHT) is arguably one of the best observation points in Maunakea, and thus, it was resolved to minimize impact on the site by redeveloping the 3.6 meter CFHT Telescope and using their former facility building and telescope pier to build and host a larger 10-meter class telescope for the MSE Project. The MSE – CFHT Corporation entrusted IDOM with the Conceptual Design of the MSE Telescope. The telescope design developed by IDOM features a novel architecture that combines well-proven and robust technologies, integrated in a telescope assembly that delivers optomechanic and mechatronic performances exceeding the 10-meter class telescopes currently in operation. The developed solution offers a very high stiffness-to-mass ratio that leads to optimal seeing performance. It also incorporates a high efficiency seismic protection system and other remarkable features.
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.010 | 0.004 |
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".