MétaCan
Menu
Back to cohort
Record W2026074296 · doi:10.1117/12.857661

Systems engineering of the Thirty Meter Telescope through integrated opto-mechanical analysis

2010· article· en· W2026074296 on OpenAlex
Scott Roberts

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueProceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE · 2010
Typearticle
Languageen
FieldPhysics and Astronomy
TopicAdaptive optics and wavefront sensing
Canadian institutionsNational Research Council Canada
FundersOntario Ministry of Research and InnovationNatural Sciences and Engineering Research Council of CanadaNational Research Council CanadaResearch and Innovation FoundationGordon and Betty Moore Foundation
KeywordsZemaxTelescopeTheodoliteMetreMATLABFinite element methodOptical engineeringComputer scienceOpticsEngineeringSoftwarePhysicsStructural engineeringAstronomy

Abstract

fetched live from OpenAlex

The merit function routine (MFR) is implemented in the National Research Council Canada Integrated Modeling (NRCIM) toolset and based in the MATLAB numerical computing environment. It links ANSYS finite element structural models with ZEMAX optical models to provide a powerful integrated opto-mechanical engineering tool. The MFR is utilized by the Thirty Meter Telescope Project to assess the telescope active optics system requirements and performance. This paper describes the MFR tool, including the interfaces to ANSYS, ZEMAX, the method of calculation of the results, and the internal data structures used. A summary of the required performance of the Thirty Meter Telescope, and the MFR results for the telescope system design are presented.

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.

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)0.001
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: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.523
Threshold uncertainty score0.996

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.010
GPT teacher head0.221
Teacher spread0.212 · 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