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Record W2051151479 · doi:10.1017/s0022215111002490

‘How does that sound?’: objective and subjective voice outcomes following CO<sub>2</sub> laser resection for early glottic cancer

2011· article· en· W2051151479 on OpenAlexaff
S E Lester, Matthew H. Rigby, Mark A. MacLean, S. Mark Taylor

Bibliographic record

VenueThe Journal of Laryngology & Otology · 2011
Typearticle
Languageen
FieldMedicine
TopicHead and Neck Cancer Studies
Canadian institutionsQueen Elizabeth II Health Sciences CentreDalhousie University
Fundersnot available
KeywordsMedicinePhonationStage (stratigraphy)Transoral laser microsurgeryCancerAudiologyGlottisProspective cohort studySurgeryMicrosurgeryLarynxLaryngeal NeoplasmInternal medicine

Abstract

fetched live from OpenAlex

OBJECTIVE: To investigate the effect of transoral laser microsurgery for early glottic cancer on subjective and objective vocal outcome measures. DESIGN: Prospective cohort study. SETTING: Tertiary care cancer centre. PARTICIPANTS: All patients scheduled for transoral laser microsurgery for untreated early primary glottic cancer over a 22-month period and offered voice assessment (31 patients; 19 tumour stage one, 12 tumour stage two). MAIN OUTCOME MEASURES: Fundamental frequency, maximum phonation time, calculated jitter, shimmer and subjective voice rating, analysed by tumour stage. RESULTS: Tumour stage T1 patients had significantly different fundamental frequencies and maximum phonation times at three months post-operatively, compared with pre-operative values; these differences resolved by 12 months. At 12 months, tumour stage T2 patients had significantly shorter maximum phonation times, and all patients reported significantly worse subjective voice ratings, compared with pre-operative values. CONCLUSION: We found no change in fundamental frequency, jitter and shimmer, one year post-operatively. Maximum phonation time deteriorated but stage one patients appeared to compensate, whereas stage two patients did not. Resection size may be a factor. All patients reported significantly worse subjective voice ratings at one year. Aerodynamic and subjective voice measures appear most sensitive to change in this patient group.

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)0.000
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 score0.038
Threshold uncertainty score0.479

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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 head0.038
GPT teacher head0.310
Teacher spread0.273 · 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

Citations13
Published2011
Admission routes1
Has abstractyes

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