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Record W3135329889 · doi:10.1016/j.pacs.2021.100257

Laser induced thermoelastic contributions from windows to signal background in a photoacoustic cell

2021· article· en· W3135329889 on OpenAlex

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.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenuePhotoacoustics · 2021
Typearticle
Languageen
FieldChemistry
TopicSpectroscopy and Laser Applications
Canadian institutionsUniversity of Toronto
FundersNatural Sciences and Engineering Research Council of CanadaNational Natural Science Foundation of ChinaNatural Science Foundation of Shaanxi ProvinceXidian UniversityChina Postdoctoral Science FoundationCanada Research Chairs
KeywordsThermoelastic dampingCollimated lightLaserSIGNAL (programming language)OpticsMaterials sciencePhotoacoustic effectRADIUSPhysicsThermal

Abstract

fetched live from OpenAlex

The existence of a signal baseline due to a variety of reasons in a photoacoustic (PA) gas measurement system is a common phenomenon. One major component is the absorption of optical windows in an enclosed PA cell. This work explores the relation between the background signal and the thermoelastic effect inside the windows by modelling the pressure and elastic wave field by means of a Green-function based method. The influence of laser incidence location, angle and radius is discussed based on a rigorous three-dimensional solid-to-fluid coupling model. The effects were theoretically demonstrated culminating in the determination of best (minimum background signal) performance using a collimated and expanded incident laser beam. The results were also validated through experiments.

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 categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
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 score0.046
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0080.000

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 head0.016
GPT teacher head0.268
Teacher spread0.252 · 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