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Record W2087068966 · doi:10.1117/12.999978

Performance of portable high-resolution Fourier transform spectrometer for trace gas remote sensing

2012· article· en· W2087068966 on OpenAlexaff
Haoyun Wei, Li-Bing Ren, Dongdong Fan, Marc‐André Soucy

Bibliographic record

VenueProceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE · 2012
Typearticle
Languageen
FieldChemistry
TopicSpectroscopy and Laser Applications
Canadian institutionsABB (Canada)
FundersChinese Academy of Sciences
KeywordsRemote sensingSpectrometerTrace gasSpectral resolutionFourier transform spectroscopyResolution (logic)Fourier transformAtmospheric compositionEnvironmental scienceFourier transform infrared spectroscopyOpticsSpectral lineAtmosphere (unit)Computer sciencePhysicsMeteorologyGeologyArtificial intelligence

Abstract

fetched live from OpenAlex

Fourier Transform Spectrometer (FTS), with its throughput, multiplex, and spectra resolution advantages, has become one of the most promising atmospheric remote-sensing instruments for the research on the global climax change and air quality evaluation. In this paper, the instrument concept and performances of a compact, portable, high resolution Fourier transform spectrometer, named B3M-FTS are reported. Sample atmospheric absorption spectra and corresponding retrieval results measured by the FTS are given. The success of atmospheric composition profile retrieval using the FTS measurements provides a useful way to understand the atmospheric chemistry, and validates the feasibility of atmospheric composition remote sensing using high resolution FTS.

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 score0.002
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.010
GPT teacher head0.228
Teacher spread0.218 · 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

Citations3
Published2012
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