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Record W2514705337 · doi:10.1117/12.2232051

Systems budgets architecture and development for the Maunakea Spectroscopic Explorer

2016· article· en· W2514705337 on OpenAlex

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.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueProceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE · 2016
Typearticle
Languageen
FieldComputer Science
TopicDistributed and Parallel Computing Systems
Canadian institutionsnot available
Fundersnot available
KeywordsSystems engineeringComputer scienceSoftware engineeringTraceabilityObservatoryProject managementIBMRequirements managementArchitectureRequirements analysisEngineeringProgramming language

Abstract

fetched live from OpenAlex

The Maunakea Spectroscopic Explorer (MSE) project is an enterprise to upgrade the existing Canada-France- Hawaii observatory into a spectroscopic facility based on a 10 meter-class telescope. As such, the project relies on engineering requirements not limited only to its instruments (the low, medium and high resolution spectrographs) but for the whole observatory. The science requirements, the operations concept, the project management and the applicable regulations are the basis from which these requirements are initially derived, yet they do not form hierarchies as each may serve several purposes, that is, pertain to several budgets. Completeness and consistency are hence the main systems engineering challenges for such a large project as MSE. Special attention is devoted to ensuring the traceability of requirements via parametric models, derivation documents, simulations, and finally maintaining KAOS diagrams and a database under IBM Rational DOORS linking them together. This paper will present the architecture of the main budgets under development and the associated processes, expand to highlight those that are interrelated and how the system, as a whole, is then optimized by modelling and analysis of the pertinent system parameters.

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: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.848
Threshold uncertainty score0.615

Codex and Gemma teacher scores by category

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

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 head0.014
GPT teacher head0.222
Teacher spread0.208 · 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