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Record W4375862352 · doi:10.3390/curroncol30050361

Recent Advances in the Surgical Management of Thyroid Cancer

2023· review· en· W4375862352 on OpenAlexvenueno aff
Boris Scheller, Dorian Culié, Gilles Poissonnet, O. Dassonville, Grégoire D’Andréa, Alexandre Bozec

Bibliographic record

VenueCurrent Oncology · 2023
Typereview
Languageen
FieldMedicine
TopicThyroid Cancer Diagnosis and Treatment
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineThyroid cancerThyroidRisk stratificationPapillary thyroid cancerMultidisciplinary approachGeneral surgeryIntensive care medicineInternal medicine

Abstract

fetched live from OpenAlex

A growing incidence of differentiated thyroid cancer (DTC) has been reported in most developed countries, corresponding mainly to incidentally discovered small papillary thyroid carcinomas. Given the excellent prognosis of most patients with DTC, optimal therapeutic management, minimizing complications, and preserving patient quality of life are essential. Thyroid surgery has a central role in both the diagnosis, staging, and treatment of patients with DTC. Thyroid surgery should be integrated into the global and multidisciplinary management of patients with DTC. However, the optimal surgical management of DTC patients is still controversial. In this review article, we discuss the recent advances and current debates in DTC surgery, including preoperative molecular testing, risk stratification, the extent of thyroid surgery, innovative surgical tools, and new surgical approaches.

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)0.001
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 score0.003
Threshold uncertainty score0.012

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.002
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.001

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 head0.265
GPT teacher head0.529
Teacher spread0.263 · 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

Citations16
Published2023
Admission routes1
Has abstractyes

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