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Record W1979087397 · doi:10.1002/lsm.20226

Raman spectroscopy for optical diagnosis in the larynx: Preliminary findings

2005· article· en· W1979087397 on OpenAlexaff
David P. Lau, Zhiwei Huang, Harvey Lui, Donald W. Anderson, Ken Berean, Murray Morrison, Liang Shen, Haishan Zeng

Bibliographic record

VenueLasers in Surgery and Medicine · 2005
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicSpectroscopy Techniques in Biomedical and Chemical Research
Canadian institutionsVancouver General HospitalUniversity of British Columbia
Fundersnot available
KeywordsLarynxRaman spectroscopyPapillomaPathologyLaryngeal NeoplasmCarcinomaMedicineOpticsAnatomyPhysics

Abstract

fetched live from OpenAlex

BACKGROUND AND OBJECTIVES: Raman spectroscopy (RS) provides information about molecular structure and is a potential tool for non-invasive tissue diagnosis. To determine if Raman spectra could be obtained rapidly from laryngeal tissue in vitro, and compare Raman spectra from normal, benign, and cancerous laryngeal tissue. STUDY DESIGN/MATERIALS AND METHODS: Forty-seven laryngeal specimens were studied using RS with signal acquisition times (SAT) between 1 and 30 second(s). Multivariate analysis was used to determine the diagnostic ability of RS compared to standard histology (n = 18, 13, and 16 respectively for normal tissue, carcinoma, and squamous papilloma). RESULTS: Good quality spectra were obtained with 5-second SAT. Spectral peak analysis showed prediction sensitivities of 89%, 69%, and 88%, and specificities of 86%, 94%, and 94% for normal tissue, carcinoma, and papilloma. CONCLUSIONS: In the larynx, spectral differences appear to exist between normal tissue, carcinoma, and papilloma. The ability to obtain spectra rapidly supports potential for future in vivo studies.

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)0.001
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 score0.305
Threshold uncertainty score0.306

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
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 head0.019
GPT teacher head0.337
Teacher spread0.318 · 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

Citations102
Published2005
Admission routes1
Has abstractyes

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