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Record W2068963225 · doi:10.1039/b503838c

Laser diode photoacoustic detection in the infrared and near infrared spectral ranges

2005· article· en· W2068963225 on OpenAlexaff
Veronika Horká, Svatopluk Civiš, Li‐Hong Xu, R. M. Lees

Bibliographic record

VenueThe Analyst · 2005
Typearticle
Languageen
FieldEngineering
TopicThermography and Photoacoustic Techniques
Canadian institutionsUniversity of New Brunswick
Fundersnot available
KeywordsOvertonePhotoacoustic spectroscopyInfraredLaserAbsorption (acoustics)Tunable diode laser absorption spectroscopyNear-infrared spectroscopyPhotoacoustic effectAnalytical Chemistry (journal)DiodeMaterials sciencePhotoacoustic imaging in biomedicineOpticsChemistryOptoelectronicsWavelengthTunable laserSpectral line

Abstract

fetched live from OpenAlex

A new technique for high resolution photoacoustic detection based on application of laser diodes has been developed. This method was tested and compared using identical photoacoustic instrumentation (cell and microphone) to study gas absorption in three different spectral regions, namely: the infrared range near 2100 cm(-1), CO and OCS fundamental band absorption; the ranges near 4200 and 4350 cm(-1), CH4, NH3 and N2O overtone and combination band absorption; the near infrared range near 6500 cm(-1), CO, CO2 and NH3 overtone absorption. Several types of diode laser operating at room temperature or at liquid nitrogen temperature were compared. The optimum gas pressures for the maximum sensitivity of the photoacoustic signals were found and the detection limits were estimated for all of the gases studied. The best sensitivity was achieved for NH3 at 100 ppbv. The sensitivity of the developed system was tested on detection of traces of NH3 and CO2 gases from car exhaust.

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: none
Teacher disagreement score0.001
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0000.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.001

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 head0.006
GPT teacher head0.199
Teacher spread0.193 · 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

Citations23
Published2005
Admission routes1
Has abstractyes

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