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Record W4399665180 · doi:10.1117/12.3019690

Overcoming obstacles to the assembly, integration, and testing of the WSS/METIS

2024· article· en· W4399665180 on OpenAlexaboutno aff
M. Filho, A. Amorim, Frederico Carvalho, P. García

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicAstronomical Observations and Instrumentation
Canadian institutionsnot available
Fundersnot available
KeywordsMetisComputer scienceSoftware engineeringSystems engineeringEngineeringWorld Wide Web

Abstract

fetched live from OpenAlex

The WSS is a subsystem being designed and manufactured by the CENTRA team (Portugal) for the ESO ELT first light instrument METIS. The WSS consists of three substructures – the support system (ELP), the alignment system (CAS), and the access and maintenance system (RIG). In total, the WSS dimensions are approximately 6 × 6 × 6 meters. In order to fully assemble, integrate, and test such a large structure, an integration hall of at least 2.5 times the WSS volume would be required to accommodate the necessary lateral and vertical clearance around WSS. Such integration halls are not readily available or accessible. In order to overcome this challenge, we have devised a 3-step strategy to assemble, integrate, and test the WSS at three different locations in three different configurations.

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)0.004
metaresearch head score (Gemma)0.004
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: none
Teacher disagreement score0.004
Threshold uncertainty score0.021

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.004
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0020.001
Open science0.0020.002
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0020.002

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 head0.020
GPT teacher head0.225
Teacher spread0.204 · 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

Citations0
Published2024
Admission routes1
Has abstractyes

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