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Record W2606741905 · doi:10.5430/jst.v7n2p23

Durable response in a thymic neuroendocrine tumor: A case report and review of the literature

2017· article· en· W2606741905 on OpenAlexvenueno aff
Yusef A. Syed, Daniel Miller, Liuyan Jiang, Arya Bagherpour, Stephen Ko

Bibliographic record

VenueJournal of Solid Tumors · 2017
Typearticle
Languageen
FieldMedicine
TopicMyasthenia Gravis and Thymoma
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineAdjuvantNeuroendocrine tumorsMetastasisAdjuvant chemotherapyChemotherapyClinical trialRadiation therapySurgical resectionPrimary tumorOncologyInternal medicineSurgeryCancer

Abstract

fetched live from OpenAlex

Thymic neuroendocrine tumors are rare, representing less than 5% of all thymic cancers, and are biologically distinct in histology and behavior. Conclusive treatment guidelines are limited due to a lack of randomized clinical trials. Current literature, consisting mainly of case reports and series, suggests that complete surgical resection combined with adjuvant radiation therapy offers the greatest survival benefit for patients with thymic neuroendocrine tumors (NET). Adjuvant chemotherapy may also delay the onset of distant metastasis. Prognosis is generally poor, particularly in high-grade tumors, as these patients are prone to early metastasis. Here we present the case of a 62-year-old woman who achieved a durable response after undergoing an aggressive multimodal treatment approach for a primary thymic NET that initially presented as chronic cough and mild dyspnea on exertion.

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)0.002
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 score0.004
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0040.003
Science and technology studies0.0010.002
Scholarly communication0.0020.002
Open science0.0020.001
Research integrity0.0030.002
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 head0.013
GPT teacher head0.306
Teacher spread0.293 · 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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