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Record W2043102022 · doi:10.1097/moo.0b013e32835cec37

The neoplastic goitre

2013· review· en· W2043102022 on OpenAlexaff
Iain J. Nixon, Ricard Simó

Bibliographic record

VenueCurrent Opinion in Otolaryngology & Head & Neck Surgery · 2013
Typereview
Languageen
FieldMedicine
TopicThyroid and Parathyroid Surgery
Canadian institutionsSt. Thomas Hospital
Fundersnot available
KeywordsMedicineMalignancyMultinodular goitreIncidence (geometry)ThyroidectomyOccultSurgeryTotal thyroidectomyRadiologyThyroidInternal medicinePathology

Abstract

fetched live from OpenAlex

PURPOSE OF REVIEW: To highlight recent advances in our understanding of the incidence of multinodular goitre (MNG) risk of malignancy, evaluation of patients with MNG, rates and factors predictive of malignancy in MNG, and the choice of surgical procedure for patients with neoplastic MNG. RECENT FINDINGS: The incidence of MNG when screened by ultrasound scanning (USS) is between 10 and 20% and when using high resolution USS can be up to 70%. The incidence of occult malignancy within MNG lies between 10 and 35% in surgical series. Younger patients and men have higher rates of malignancy, as do patients with a family history, prior irradiation and those with signs of compressive or invasive disease. Subtotal thyroidectomy has been rejected in favour of either total lobectomy or total thyroidectomy for most patients with MNG. SUMMARY: An increasing number of patients with MNG will be encountered in surgical practice. Most patients can be cured with total lobectomy or total thyroidectomy, which minimizes recurrence rates and ensures an oncological approach to patients with incidentally discovered malignancy within MNG.

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)0.000
metaresearch head score (Gemma)0.001
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: Review · Consensus signal: Review
Teacher disagreement score0.005
Threshold uncertainty score0.017

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0030.002
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0050.002

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 head0.112
GPT teacher head0.388
Teacher spread0.275 · 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
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

Citations14
Published2013
Admission routes1
Has abstractyes

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