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Record W2932157548 · doi:10.3899/jrheum.181024

Gynecologic Vasculitis: Positron Emission Tomography–Computed Tomography Contribution in a Rare Localization of Giant Cell Arteritis

2019· letter· en· W2932157548 on OpenAlexvenueno aff
Marie-Charlotte Besse, Nived Collercandy, Élisabeth Diot

Bibliographic record

VenueThe Journal of Rheumatology · 2019
Typeletter
Languageen
FieldMedicine
TopicVasculitis and related conditions
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineGiant cell arteritisPositron emission tomographyVasculitisPositron Emission Tomography-Computed TomographyTomographyRadiologyComputed tomographyArteritisNuclear medicinePathology

Abstract

fetched live from OpenAlex

We read with great interest the letter entitled “Unusual presentation of giant cell arteritis in 2 patients: uterine involvement,” published in The Journal of Rheumatology 1. We have observed a case of ovarian involvement of giant cell arteritis (GCA) whose characteristics allow us to reinforce some key messages regarding the investigation of inflammatory disorders. A 67-year-old female (who has given her written informed consent to … Address correspondence to Dr. E. Diot, Service de Médecine Interne, CHRU de Tours, Hôpital Bretonneau, 2 Boulevard Tonnellé, 37000 Tours, France. E-mail: elisabeth.diot{at}univ-tours.fr

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)0.005
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: Empirical
Teacher disagreement score0.012
Threshold uncertainty score0.012

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.005
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.001
Science and technology studies0.0020.002
Scholarly communication0.0010.002
Open science0.0010.001
Research integrity0.0120.005
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 head0.005
GPT teacher head0.212
Teacher spread0.207 · 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

Citations4
Published2019
Admission routes1
Has abstractyes

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