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Record W2140982419 · doi:10.1002/hed.23757

Transoral robotic excision of ectopic lingual thyroid: Case series and literature review

2014· review· en· W2140982419 on OpenAlexaff
Eitan Prisman, Alexis Patsias, Eric M. Genden

Bibliographic record

VenueHead & Neck · 2014
Typereview
Languageen
FieldMedicine
TopicHead and Neck Anomalies
Canadian institutionsVancouver General HospitalUniversity of British Columbia
Fundersnot available
KeywordsEctopic thyroidSeries (stratigraphy)ThyroidMedicineSurgical excisionGeneral surgerySurgeryInternal medicineBiology

Abstract

fetched live from OpenAlex

BACKGROUND: Surgical excision of an ectopic lingual thyroid has traditionally been associated with significant morbidity and has therefore been reserved for patients with severe obstructive symptoms or suspected malignancy. Transoral robotic surgery (TORS) has provided a minimally invasive approach to completely and safely excise ectopic lingual thyroid. METHODS: Three index cases were identified from the detailed clinical database of TORS patients. A systematic review of the management of ectopic lingual thyroid in the English literature was performed. RESULTS: TORS-assisted excision of a lingual thyroid gland was successfully performed in 3 patients with excellent functional outcomes CONCLUSION: TORS-assisted excision of an ectopic lingual thyroid is a safe and feasible treatment modality with minimal morbidity, and, in experienced hands, should be offered as a valid treatment for this pathology.

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)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Case report · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.007
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0070.006
Science and technology studies0.0010.001
Scholarly communication0.0010.002
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.001

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 head0.042
GPT teacher head0.370
Teacher spread0.329 · 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 designCase report
Domainnot available
GenreReview

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

Citations31
Published2014
Admission routes1
Has abstractyes

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