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Record W2839161634 · doi:10.1117/12.2314266

Maunakea Spectroscopic Explorer (MSE): instrumentation suite

2018· article· en· W2839161634 on OpenAlexaboutno aff
Kei Szeto, Alexis Hill, Nicolas Flagey, Alan W. McConnachie, Richard Murowinski

Bibliographic record

VenueGround-based and Airborne Instrumentation for Astronomy VII · 2018
Typearticle
Languageen
FieldPhysics and Astronomy
TopicAstronomy and Astrophysical Research
Canadian institutionsnot available
Fundersnot available
KeywordsSpectrographSuiteInstrumentation (computer programming)TelescopeInterface (matter)Computer scienceCalibrationSystems engineeringFocus (optics)Spectral resolutionTransmission (telecommunications)Remote sensingOpticsPhysicsEngineeringOperating systemTelecommunicationsAstronomySpectral line

Abstract

fetched live from OpenAlex

The Maunakea Spectroscopic Explorer (MSE) is replacement of the existing 3.6-m Canada France Hawaii Telescope into a dedicated wide field highly multiplexed fiber fed spectroscopic facility. MSE is capable of observing over four thousand science targets simultaneously in two resolution modes. The paper describes the unique instrument system capabilities and its components starting from the telescope prime focus and ending at the spectrograph suite. The instrument system components have completed their conceptual designs and they include a Sphinx positioner system, fiber transmission system, low/moderate resolution and high resolution spectrographs and a calibration system. These components will be procured separately and the Project is responsible for their integration and the overall system performance afterward. The paper describes from a system perspective the specific design and interface constraints imposed on the components given the extra interface and integration considerations.

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 categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.893
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.018
GPT teacher head0.290
Teacher spread0.272 · 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.

Study designOther design
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

Citations10
Published2018
Admission routes1
Has abstractyes

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