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Record W1988621109 · doi:10.1117/12.670379

SHIFTS: simulator for the Herschel imaging Fourier transform spectrometer

2006· article· en· W1988621109 on OpenAlexaff
John V. Lindner, David A. Naylor, B. M. Swinyard

Bibliographic record

VenueProceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE · 2006
Typearticle
Languageen
FieldChemistry
TopicSpectroscopy and Laser Applications
Canadian institutionsUniversity of Lethbridge
Fundersnot available
KeywordsSpire (mollusc)SpectrometerComputer scienceSpace observatoryGraphical user interfaceImaging spectrometerInterface (matter)Remote sensingSoftwareObservatorySpectral resolutionFourier transformComputer graphics (images)SimulationComputer hardwareOpticsInfraredPhysicsOperating systemAstronomySpectral lineGeology

Abstract

fetched live from OpenAlex

The Spectral and Photometric Imaging Receiver (SPIRE) is one of three scientific instruments on the European Space Agency's (ESA) Herschel Space Observatory (HSO). The medium resolution spectroscopic capabilities of SPIRE are provided by an imaging Fourier transform spectrometer (IFTS). A software simulator of the SPIRE IFTS was written to create realistic data products, making use of available qualification and test data. A graphical user interface (GUI) provides fast and flexible access to the simulation engine. We present the design and integration of the simulator, as well as results from the simulator predicting the instrument performance under varying operational conditions.

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)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Software · Consensus signal: none
Teacher disagreement score0.015
Threshold uncertainty score0.050

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0030.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0150.004

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 head0.007
GPT teacher head0.232
Teacher spread0.224 · 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 designSimulation or modeling
Domainnot available
GenreSoftware

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

Citations2
Published2006
Admission routes1
Has abstractyes

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Same venueProceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIESame topicSpectroscopy and Laser ApplicationsFrench-language works237,207