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Record W2066426796 · doi:10.1063/1.3103570

Laser induced thermal-wave fields in bilayered spherical solids

2009· article· en· W2066426796 on OpenAlexaff
Guangxi Xie, Zhifeng Chen, Chinhua Wang, Andreas Mandelis

Bibliographic record

VenueReview of Scientific Instruments · 2009
Typearticle
Languageen
FieldEngineering
TopicThermography and Photoacoustic Techniques
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsThermal diffusivityMaterials scienceOpticsThermalLaserLaser flash analysisField (mathematics)Photothermal therapyThermal conductionPhysicsComposite materialThermodynamics

Abstract

fetched live from OpenAlex

We present a theoretical model for evaluating solid bilayered spherical samples (surfaces) that are heated by a frequency modulated light beam generating thermal waves. The Green's function method is used as it provides a way of evaluating thermal-wave fields of bilayered spherical structures with arbitrary intensity distributions of incident laser beams. The specific thermal-wave Green's function corresponding to the composite structure has been derived. The characteristics of the thermal-wave field with respect to the thermal diffusivity of the material, the diameter of the sample, the size of the incident beam, and the polar angle at which the thermal-wave field is measured on the surface are presented. Experimental results obtained with laser infrared photothermal radiometry are fitted to the theory and the thermal diffusivities of steel spheres are deduced.

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 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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.903
Threshold uncertainty score0.481

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 integrity0.0000.000
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 head0.021
GPT teacher head0.250
Teacher spread0.229 · 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 teacher head, 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

Citations10
Published2009
Admission routes1
Has abstractyes

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