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Record W2036956020 · doi:10.1142/s0129156408005321

PASSIVE STANDOFF DETECTION OF SURFACE CONTAMINANTS: A NOVEL APPROACH BY DIFFERENTIAL POLARIZATION FTIR SPECTROMETRY

2008· article· en· W2036956020 on OpenAlex
Jean‐Marc Thériault, Hugo Lavoie, Eldon Puckrin, François Bouffard

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueInternational Journal of High Speed Electronics and Systems · 2008
Typearticle
Languageen
FieldChemistry
TopicSpectroscopy and Laser Applications
Canadian institutionsDefence Research and Development Canada
Fundersnot available
KeywordsRadiancePolarization (electrochemistry)Fourier transform infrared spectroscopySkyMaterials scienceMass spectrometryOpticsRemote sensingFourier transformEnvironmental scienceAnalytical Chemistry (journal)OptoelectronicsPhysicsChemistryEnvironmental chemistryGeologyMeteorologyChromatography

Abstract

fetched live from OpenAlex

An approach for the passive standoff detection of surface contaminants by differential polarization FTIR spectrometry is proposed. The surface radiance modeling associated with the method is given. Unpolarized and polarized sensing measurements obtained with the CATSI sensor for the standoff detection of liquid agent VX deposited on high-reflectivity surfaces are presented. The analysis of results indicates that the differential polarization approach is well suited to mitigate sky radiance drifts, which favours unambiguous surface contaminant detections. An experimental and modeling study initiated to address the spectral polarization phenomenology is outlined. The design of an optimized FTIR sensor for differential polarization spectrometry measurements is discussed.

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.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.063
Threshold uncertainty score0.577

Codex and Gemma teacher scores by category

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

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 head0.008
GPT teacher head0.229
Teacher spread0.221 · 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