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Record W2591255127

FROM MICROLARYNGOSCOPY TO FLUORESCENCE LARYNGEAL ENDOSCOPY

2002· article· en· W2591255127 on OpenAlexaboutno aff
Miha Žargi, Igor Fajdiga, Lojze Šmid

Bibliographic record

VenueDOAJ (DOAJ: Directory of Open Access Journals) · 2002
Typearticle
Languageen
FieldMedicine
TopicTracheal and airway disorders
Canadian institutionsnot available
Fundersnot available
KeywordsEndoscopyLaryngoscopyMedicineSurgeryIntubation
DOInot available

Abstract

fetched live from OpenAlex

Tissue fluorescence induced by a specific wavelength without photodynamic markers offers new possibilities for the detection and localization of early laryngeal carcinoma. The recognition of cancer is possible with a specially designed system (LIFE, Xillix Co., Richmond, Canada) that displays different fluorescent properties of normal and cancerous tissues on a video monitor. 108 patients (in 74 of whom malignancy was suspected) were included in the study. The laryngoscopic appearance obtained by microlaryngoscopy was compared to the fluorescence image and the pathohistological findings of the observed sites. The results of the study show that detection of laryngeal malignancies with fluorescence laryngoscopy is more effective than with standard microlaryngoscopy and that recognition is even more successful if the two methods are used in combination.

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)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.004
Threshold uncertainty score0.013

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.001
Science and technology studies0.0000.002
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0010.002
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 head0.198
GPT teacher head0.520
Teacher spread0.322 · 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 designNot applicable
Domainnot available
GenreMethods

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

Citations1
Published2002
Admission routes1
Has abstractyes

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Same venueDOAJ (DOAJ: Directory of Open Access Journals)Same topicTracheal and airway disordersFrench-language works237,207