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Record W4412937596 · doi:10.1007/s00405-025-09609-0

European Laryngological Society consensus statement on optimal monitoring schedules after treatment for early glottic cancer: a risk-stratification

2025· article· en· W4412937596 on OpenAlexaff
Małgorzata Wierzbicka, Agatha Baidun, Andy Bertolin, Marco Lionello, Giovanni Succo, Berit M. Verbist, Davide Farina, Martine Hendriksma, Marc Remacle, Ricard Simó, Elisabeth V. Sjögren, Cesare Piazza

Bibliographic record

VenueEuropean Archives of Oto-Rhino-Laryngology · 2025
Typearticle
Languageen
FieldMedicine
TopicHead and Neck Cancer Studies
Canadian institutionsSurgical Specialties (Canada)
Fundersnot available
KeywordsMedicineRisk stratificationIntensive care medicinePsychological interventionMedical physicsStatement (logic)Risk analysis (engineering)Internal medicine

Abstract

fetched live from OpenAlex

Early glottic cancer has an excellent prognosis provided that recurrences are detected in a timely manner. However, current guidelines lack specific recommendations for intervals or interventions during follow-up, and primarily advocate surveillance in the most advanced stages where the benefits are actually the lowest. This consensus statement introduces a risk-stratification-guided follow-up schedule for T1-T2N0 patients, aiming to optimize oncologic and functional outcomes while ensuring early detection of residual or recurrent disease to preserve organ function. Separate protocols are outlined for surgical and non-surgical patients, including endoscopic examination, radiological imaging, and thyroid function screening. Also, the pathway to reach this routine observation phase is described, specifying the criteria and timing of a second-look microlaryngoscopy.

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)0.028
metaresearch head score (Gemma)0.032
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: Not applicable
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.028
Threshold uncertainty score0.147

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0280.032
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.004
Bibliometrics0.0020.001
Science and technology studies0.0010.001
Scholarly communication0.0020.002
Open science0.0040.003
Research integrity0.0060.006
Insufficient payload (model declined to judge)0.0030.003

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 head0.034
GPT teacher head0.327
Teacher spread0.293 · 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
GenreOther

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

Citations0
Published2025
Admission routes1
Has abstractyes

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