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Record W2088159530 · doi:10.1364/ol.33.000711

Development and preliminary results of an endoscopic Raman probe for potential in vivo diagnosis of lung cancers

2008· article· en· W2088159530 on OpenAlexaff
Michael Short, Stephen Lam, Annette McWilliams, Jianhua Zhao, Harvey Lui, Haishan Zeng

Bibliographic record

VenueOptics Letters · 2008
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicSpectroscopy Techniques in Biomedical and Chemical Research
Canadian institutionsOccupational Cancer Research CentreCanadian Centre for Applied Research in Cancer ControlBC Cancer Agency
Fundersnot available
KeywordsRaman spectroscopyOpticsMaterials scienceOptical fiberRaman scatteringFiberSpectrometerLaserFiber laserPhysics

Abstract

fetched live from OpenAlex

A near-infrared Raman system was developed to collect real-time in vivo human lung spectra. The excitation light and the emission were guided to and from the tissue surface by a reusable fiber catheter passed down the instrument channel of a bronchoscope. Two-stage filtering was used to reduce laser noise, fluorescence, and Raman emissions from the fibers. A second fiber bundle guided the emission to a spectrometer where the fibers, in a round packing geometry, were spread out to form a parabolic arc that improved the signal-to-noise ratio 20-fold, facilitating real-time spectral measurements. Preliminary clinical tests show that clear and reliable Raman spectra can be obtained.

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)0.002
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 score0.011

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.012
GPT teacher head0.288
Teacher spread0.277 · 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

Citations147
Published2008
Admission routes1
Has abstractyes

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