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Record W2735522662 · doi:10.1530/erc-17-0209

A comprehensive review on MEN2B

2017· review· en· W2735522662 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueEndocrine Related Cancer · 2017
Typereview
Languageen
FieldMedicine
TopicRadiomics and Machine Learning in Medical Imaging
Canadian institutionsQueen's University
Fundersnot available
KeywordsComputer science

Abstract

fetched live from OpenAlex

MEN2B is a very rare autosomal dominant hereditary tumor syndrome associated with medullary thyroid carcinoma (MTC) in 100% cases, pheochromocytoma in 50% cases and multiple extra-endocrine features, many of which can be quite disabling. Only few data are available in the literature. The aim of this review is to try to give further insights into the natural history of the disease and to point out the missing evidence that would help clinicians optimize the management of such patients. MEN2B is mainly characterized by the early occurrence of MTC, which led the American Thyroid Association to recommend preventive thyroidectomy before the age of 1 year. However, as the majority of mutations are de novo , improved knowledge of the nonendocrine signs would help to lower the age of diagnosis and improve long-term outcomes. Future large-scale studies will be aimed at characterizing more in detail the main characteristics and outcomes of MEN2B.

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.

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 categoriesMeta-epidemiology (narrow), Research integrity, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.861
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0040.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.003
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 head0.099
GPT teacher head0.470
Teacher spread0.371 · 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