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Record W2478142606 · doi:10.1117/12.2234471

Maunakea Spectroscopic Explorer: the status and progress of a major site redevelopment project

2016· article· en· W2478142606 on OpenAlexaffabout
Rick Murowinski, D. A. Simons, Alan W. McConnachie, Kei Szeto

Bibliographic record

VenueProceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE · 2016
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicGeological and Geophysical Studies
Canadian institutionsHerzberg Institute of Astrophysics
Fundersnot available
KeywordsRedevelopmentComputer scienceEngineeringAstrobiologyCivil engineeringPhysics

Abstract

fetched live from OpenAlex

The Maunakea Spectroscopic Explorer (MSE) project is a collaboration designing the largest non-ELT optical/NIR astronomical telescope to date. MSE is unique as a major astronomical facility since it involves the redevelopment of an existing facility, that of the Canada France Hawai‘i Telescope (CFHT), with a newly expanded partnership. The project office is hosted at CFHT in Waimea HI, and includes new partners from Australia, China, India and Spain. The project is being developed by an international collaboration with design team membership distributed across four continents. In addition to a report on the progress and organization of design work, this paper describes the challenges of redeveloping a major astronomical site in Hawai‘i. We discuss the Project Office and engineering work from the aspects of meeting the Science Requirements while satisfying the unique conditions imposed by redevelopment on Maunakea.

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 imitation

Not 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.

metaresearch head score (Codex)0.011
metaresearch head score (Gemma)0.006
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.012
Threshold uncertainty score0.059

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0110.006
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0040.003
Open science0.0030.002
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0050.001

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 head0.013
GPT teacher head0.212
Teacher spread0.200 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
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

Citations21
Published2016
Admission routes2
Has abstractyes

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Same venueProceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIESame topicGeological and Geophysical StudiesFrench-language works237,207