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Record W2104622330 · doi:10.1044/vvd22.1.25

Laryngectomy – Concepts and Shifting Paradigms

2012· article· en· W2104622330 on OpenAlexaff
Jason Xu, Kevin Fung

Bibliographic record

VenuePerspectives on Voice and Voice Disorders · 2012
Typearticle
Languageen
FieldMedicine
TopicHead and Neck Cancer Studies
Canadian institutionsWestern University
Fundersnot available
KeywordsTransoral laser microsurgeryLaryngectomyMedicineRadiation therapySurgeryMicrosurgeryGeneral surgeryCancerLarynxHypopharyngeal cancerInternal medicine

Abstract

fetched live from OpenAlex

The treatment of laryngeal cancer has changed substantially over the past 50 years with advances that maximize both oncological and functional outcomes. Surgically, transoral laser microsurgery and transoral robotic surgery are minimally invasive endoscopic techniques that have evolved from the conventional open partial laryngectomy and total laryngectomy. Along with concurrent advances in organ preservation radiotherapy and chemotherapy, choosing the best treatment for laryngeal cancer has become more complex. In this paper, we present a brief overview of laryngeal cancer and review the management options currently available, with a focus on advances in surgery. This information is critical for speech-language pathologists to understand as they participate on multidiscliplinary rehabilitation teams with this population.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.071
Threshold uncertainty score0.675

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 head0.018
GPT teacher head0.326
Teacher spread0.308 · 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 designObservational
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

Citations1
Published2012
Admission routes1
Has abstractyes

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