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Record W2154066210 · doi:10.1117/1.jbo.18.3.031109

Calibrating the measurement of wavelength-dependent second harmonic generation from biological tissues with a BaB2O4 crystal

2013· article· en· W2154066210 on OpenAlexafffund
Mengzhe Shen, Jianhua Zhao, Haishan Zeng, Shuo Tang

Bibliographic record

VenueJournal of Biomedical Optics · 2013
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicSpectroscopy Techniques in Biomedical and Chemical Research
Canadian institutionsBC Cancer AgencyUniversity of British Columbia
FundersUniversity of British Columbia Graduate SchoolNatural Sciences and Engineering Research Council of Canada
KeywordsSecond-harmonic generationOpticsWavelengthMaterials scienceNonlinear opticsCrystal (programming language)OptoelectronicsBiological imagingHarmonicPhysicsComputer scienceLaserFluorescence

Abstract

fetched live from OpenAlex

Although second harmonic generation (SHG) imaging has emerged as a powerful tool for imaging biological tissues with submicron resolution, the excitation wavelength dependence of SHG intensity in biological tissues is an optical property that is not fully understood so far. We first calibrate system factors which may potentially affect the accuracy of the wavelength-dependent SHG measurement. Then our calibration is validated by measuring the wavelength dependence of SHG signal from a BaB₂O₄ crystal under different focusing conditions and comparing with the theoretical calculations. The good agreement between the experimental results and theoretical calculations demonstrates that we have established a reliable method to validate wavelength-dependent SHG measurement over a broad wavelength range. We also investigate the wavelength dependence of a 10-μm thick mouse tendon tissue in both forward and backward directions. It is found that SHG of mouse tendon tissue decreases monotonically for excitation from 750 to 950 nm.

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)0.001
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 score0.006
Threshold uncertainty score0.473

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
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 head0.028
GPT teacher head0.281
Teacher spread0.253 · 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
Published2013
Admission routes2
Has abstractyes

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