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Record W2082713603 · doi:10.1063/1.4727877

Dual beam photoacoustic infrared spectroscopy of solids using an external cavity quantum cascade laser

2012· article· en· W2082713603 on OpenAlexaff
M. Dehghany, Kirk H. Michaelian

Bibliographic record

VenueReview of Scientific Instruments · 2012
Typearticle
Languageen
FieldChemistry
TopicSpectroscopy and Laser Applications
Canadian institutionsNatural Resources Canada
Fundersnot available
KeywordsQuantum cascade laserMaterials scienceLaserPhotoacoustic spectroscopyOpticsInfraredAbsorption (acoustics)Infrared spectroscopyAbsorption spectroscopySpectroscopyCascadeContinuous wavePhotoacoustic effectAnalytical Chemistry (journal)OptoelectronicsPhysicsChemistry

Abstract

fetched live from OpenAlex

Quantum cascade laser-based instrumentation for dual beam photoacoustic (PA) spectroscopy is described in this article. Experimental equipment includes a 4.55 μm (2141-2265 cm(-1)) continuous wave external cavity quantum cascade laser (EC-QCL), two gas-microphone PA cells, and two lock-in amplifiers. Correction for the time and wavenumber dependence of the laser output is effected through real-time division of the PA signals derived from the sample and reference channels. Source-compensated mid-infrared absorption spectra of carbon black powder and aromatic hydrocarbon solids were obtained to confirm the reliability of the method. Absorption maxima in the EC-QCL PA spectra of hydrocarbons are better defined than those in Fourier transform infrared spectra acquired under similar conditions, enabling the detection of several previously unknown bands.

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)0.000
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 score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.001
Research integrity0.0010.001
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 head0.030
GPT teacher head0.319
Teacher spread0.289 · 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

Citations5
Published2012
Admission routes1
Has abstractyes

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