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Record W1991617824 · doi:10.1364/ol.29.000587

Integrated endoscopy system for simultaneous imaging and spectroscopy for early lung cancer detection

2004· article· en· W1991617824 on OpenAlexaff
Haishan Zeng, Mirjan Petek, Marjeta Tercelj Zorman, Annette McWilliams, Branko Palcic, Stephen Lam

Bibliographic record

VenueOptics Letters · 2004
Typearticle
Languageen
FieldMedicine
TopicLung Cancer Diagnosis and Treatment
Canadian institutionsBC Cancer Agency
Fundersnot available
KeywordsOpticsAutofluorescenceSpectroscopyMedical imagingWhite lightEndoscopyFluorescence spectroscopyImaging spectroscopyMaterials scienceBiomedical engineeringComputer sciencePhysicsMedicineFluorescenceArtificial intelligenceRadiology

Abstract

fetched live from OpenAlex

An integrated endoscopy system for simultaneous imaging and spectroscopy was developed to facilitate more accurate and convenient detection of early lung cancers. A specially designed three-CCD camera in combination with a dedicated light source permits capture of both white-light color images and tissue autofluorescence images without the need to switch between two different cameras. A mirror with an optical fiber at its center, placed at an interim imaging plane inside the camera unit, facilitates simultaneous imaging and spectroscopy measurements in either white-light reflectance mode or fluorescence mode. The system has been successfully tested in a clinic, demonstrating a practical approach to improve both diagnostic sensitivity and specificity at the same time.

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)0.001
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: none
Teacher disagreement score0.004
Threshold uncertainty score0.012

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.001

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 head0.006
GPT teacher head0.273
Teacher spread0.267 · 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

Citations43
Published2004
Admission routes1
Has abstractyes

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