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Record W2601854164 · doi:10.7759/cureus.1115

Adjuvant Radiotherapy for Thymic Neuroendocrine Tumors: A Case Report and Review of the Literature

2017· article· en· W2601854164 on OpenAlexaff
Omar Iskanderani, David Roberge, Geneviève Coulombe

Bibliographic record

VenueCureus · 2017
Typearticle
Languageen
FieldMedicine
TopicMyasthenia Gravis and Thymoma
Canadian institutionsMcGill University Health CentreCentre Hospitalier de l’Université de Montréal
Fundersnot available
KeywordsMedicineAdjuvant radiotherapyAdjuvantRadiation therapyIncidence (geometry)Carcinoid tumorsNeuroendocrine tumorsEndocrine systemNeuroendocrine tumourResectionOncologyInternal medicinePathologyGeneral surgerySurgeryHormone

Abstract

fetched live from OpenAlex

Thymic carcinoid tumors are very rare. Between two and four percent of carcinoids originate from the thymus with an estimated incidence of 1.5 to 3 per 10,000,000 persons per year. Thymic carcinoids can be associated with the multiple endocrine neoplasia (MEN) type 1. The principal treatment is surgical resection. The potential roles of systemic and radiation treatments are a matter of debate. We describe the successful multidisciplinary treatment of a case of thymic carcinoid associated with MEN and review the literature pertaining to the use of adjuvant thoracic radiation.

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: Case report · Consensus signal: Case report
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.005
Threshold uncertainty score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0050.004
Science and technology studies0.0010.001
Scholarly communication0.0010.003
Open science0.0020.001
Research integrity0.0040.002
Insufficient payload (model declined to judge)0.0030.002

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 head0.021
GPT teacher head0.325
Teacher spread0.304 · 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
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

Citations0
Published2017
Admission routes1
Has abstractyes

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