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Record W2802141134 · doi:10.24953/turkjped.2017.05.014

Child with RET proto-oncogene codon 634 mutation

2017· article· en· W2802141134 on OpenAlexaff
Dilek İnce, Kamer Mutafoğlu, Erdener Özer, Ayhan Abacı, Fılız Hazan, Osman Zeki Karakuş, Hale Tuhan, Yeşim Oymak, Eda Ataseven, Bengü Demirağ, Nur Olgun

Bibliographic record

VenueThe Turkish Journal of Pediatrics · 2017
Typearticle
Languageen
FieldMedicine
TopicThyroid Cancer Diagnosis and Treatment
Canadian institutionsPediatric Oncology Group
Fundersnot available
KeywordsMedicineMutationRET proto-oncogeneThyroid carcinomaLymph nodeThyroidectomyThyroidCalcitoninPathologyGastroenterologyInternal medicineCancer researchGeneGermline mutationGeneticsBiology

Abstract

fetched live from OpenAlex

İnce D, Demirağ B, Ataseven E, Oymak Y, Tuhan H, Karakuş OZ, Hazan F, Abacı A, Özer E, Mutafoglu K, Olgun N. Child with RET proto-oncogene codon 634 mutation. Turk J Pediatr 2017; 59: 590-593. Herein we reported a 7-year-old child with RET proto-oncogene c634 mutation. Her mother had been diagnosed with medullary thyroid carcinoma (MTC), and treated six years ago. Heterozygous mutation of the RET proto-oncogene at c634 had been detected in her mother. Genetic analysis showed the presence of the same mutation in our patient. Thyroid functions were normal. Serum calcitonin level was found mildly elevated. Parathormone (PTH) and carcinoembrionic antigen (CEA) levels were normal. Prophylactic thyroidectomy and sampling of cervical lymph nodes were performed. Histopathologic examination revealed hyperplasia in thyroid C cells, and reactive lymphadenopathy. The risk of MTC has been reported 100% through the life of patients with RET proto-oncogene mutation. It has been reported that particularly patients with c634 mutation have more risk of occurence of metastatic and progressive/recurrent MTC. Prophylactic `thyroidectomy, cervical lymph node dissection` before 5-years-of-age should be considered for these patients.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.148
Threshold uncertainty score0.260

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.015
GPT teacher head0.280
Teacher spread0.265 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
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

Citations1
Published2017
Admission routes1
Has abstractyes

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