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Record W4384652382 · doi:10.1002/asna.20230108

The Maunakea Spectroscopic Explorer: Thousands of fibers, infinite possibilities

2023· article· en· W4384652382 on OpenAlexaboutno aff
Andrew Sheinis, Samuel C. Barden, Jennifer Sobeck

Bibliographic record

VenueAstronomische Nachrichten · 2023
Typearticle
Languageen
FieldPhysics and Astronomy
TopicAstronomy and Astrophysical Research
Canadian institutionsnot available
FundersDepartment of Electronics and Information Technology, Ministry of Communications and Information Technology
KeywordsPhysicsGalaxyAstronomyAstrophysicsUniverseRedshiftMilky WayTelescopeSpectral resolutionGalaxy formation and evolutionSkyPathfinderSpectral line

Abstract

fetched live from OpenAlex

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.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.400
Threshold uncertainty score0.822

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.001

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.

Opus teacher head0.015
GPT teacher head0.277
Teacher spread0.262 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations4
Published2023
Admission routes1
Has abstractyes

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