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Record W2063323797 · doi:10.1117/12.828044

Performances of the SAC-D NIRST flight model radiometer

2009· article· en· W2063323797 on OpenAlexaffabout
Mélanie Leclerc, Linda Marchese, Patrice Côté, François Châteauneuf, C. Chevalier, H. G. Marraco, Linh Ngo Phong

Bibliographic record

VenueProceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE · 2009
Typearticle
Languageen
FieldEngineering
TopicCalibration and Measurement Techniques
Canadian institutionsCanadian Space AgencyInstitut National d'Optique
FundersComisión Nacional de Actividades EspacialesNational Aeronautics and Space Administration
KeywordsMicrobolometerRadiometerComputer scienceKey (lock)Baseline (sea)Remote sensingInternational Space StationSpace technologyInfraredSystems engineeringAerospace engineeringBolometerTelecommunicationsPhysicsOpticsEngineeringDetectorComputer securityGeology

Abstract

fetched live from OpenAlex

Aquarius/SAC-D is a cooperative international mission conducted jointly by the National Aeronautics and Space Administration of the United States of America and the Comisión Nacional de Actividades Espaciales of Argentina. Jointly developed by CONAE and the Canadian Space Agency, the New IR Sensor Technology (NIRST) instrument will monitor high temperature events. NIRST has one band in the mid-wave infrared and two bands in the thermal infrared. The baseline design of the NIRST is based on microbolometer technology developed jointly by INO and the CSA. This paper will first present an overview of the design of the NIRST camera module. The manufacturing and qualification activities for the Flight Model will be described and key performance parameters, as measured during the verification campaign, will be reported.

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)0.001
metaresearch head score (Gemma)0.001
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: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.004
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0020.001

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 head0.217
Teacher spread0.203 · 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

Citations9
Published2009
Admission routes2
Has abstractyes

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Same venueProceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIESame topicCalibration and Measurement TechniquesFrench-language works237,207