MétaCan
Menu
Back to cohort
Record W2963593225 · doi:10.1117/12.2536193

OPSys: optical payload systems facility for space instrumentation integration and calibration

2019· article· en· W2963593225 on OpenAlexaboutno aff
Gerardo Capobianco, Silvano Fineschi, G. Massone, Federico Landini, Marta Casti, Alessandro Bellomo, Maurizio Deffacis, M. Romoli, E. Antonucci, V. Andretta, G. Naletto, G. Nicolini, D. Spadaro

Bibliographic record

VenueInternational Conference on Space Optics — ICSO 2018 · 2019
Typearticle
Languageen
FieldEngineering
TopicCalibration and Measurement Techniques
Canadian institutionsnot available
Fundersnot available
KeywordsCoronagraphPayload (computing)CalibrationStray lightAerospaceOpticsInstrumentation (computer programming)Aerospace engineeringRemote sensingPhysicsEngineeringComputer scienceAstronomyExoplanetPlanet

Abstract

fetched live from OpenAlex

The Optical Payload System (OPSys) is an INAF (italian National Institute for Astrophysics) facility hosted by Aerospace Logistics Technology Engineering Company (ALTEC SpA) in Turin, Italy. The facility is composed by three clean rooms having different cleanliness levels, a thermo-vacuum chamber (SPOCC, Space Optics calibration Chamber) with a motorized optical bench and several light sources covering the range from the extreme ultraviolet to the red light wavelengths. The SPOCC has been designed having in mind the very stringent requirements of the calibration of solar coronagraphs and the suppression of the stray-light. The facility and the optical performances will be described here. The calibration campaign performed on Metis space coronagraph will be reported as a case study.

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)0.003
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: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.022
Threshold uncertainty score0.073

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0030.002
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0220.010

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 head0.043
GPT teacher head0.278
Teacher spread0.235 · 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 designBench or experimental
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

Citations4
Published2019
Admission routes1
Has abstractyes

Explore more

Same venueInternational Conference on Space Optics — ICSO 2018Same topicCalibration and Measurement TechniquesFrench-language works237,207