MétaCan
Menu
Back to cohort
Record W4285489880 · doi:10.1117/12.2629379

The METIS warm support structure final design

2022· article· en· W4285489880 on OpenAlexaboutno aff
Ricardo Costa, A. Amorim, André Boné, M. Filho, Frederico Carvalho, Marcelino Ngando, P. García

Bibliographic record

VenueGround-based and Airborne Instrumentation for Astronomy IX · 2022
Typearticle
Languageen
FieldPhysics and Astronomy
TopicAdaptive optics and wavefront sensing
Canadian institutionsnot available
Fundersnot available
KeywordsCryostatHexapodMetisComputer scienceInterface (matter)Operating systemPhysicsWorld Wide WebRobot

Abstract

fetched live from OpenAlex

This article presents the final design of the METIS/ELT warm support structure subsystem. The warm support structure provides the mechanical interface between the cryostat and the Nasmyth platform. It consists of three substructures: the elevation platform, the cryostat alignment structure (CAS), and the instrument access platform. The elevation platform is connected to the Nasmyth platform and holds the CAS. It consists of seven legs connected to three notes. The CAS is a hexapod holding the cryostat, allowing maintenance, alignment, and positioning. The instrument access platform allows human access to the cryostat, it holds the cable support system and is prepared to support the future Single Laser Adaptive Optics system. The subsystem requirements, design trade-offs, interface considerations, final design and simulation results of the substructures will be detailed as presented to the METIS Final Design Review, in 2022.

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)0.002
metaresearch head score (Gemma)0.002
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: Methods · Consensus signal: Methods
Teacher disagreement score0.025
Threshold uncertainty score0.084

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.000
Science and technology studies0.0010.000
Scholarly communication0.0020.001
Open science0.0020.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0250.016

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 head0.022
GPT teacher head0.247
Teacher spread0.225 · 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
GenreMethods

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
Published2022
Admission routes1
Has abstractyes

Explore more

Same venueGround-based and Airborne Instrumentation for Astronomy IXSame topicAdaptive optics and wavefront sensingFrench-language works237,207