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Record W2116788334 · doi:10.3899/jrheum.120317

Arteriosclerosis or Vasculitis? Color Duplex Sonography in Giant Cell Arteritis

2012· letter· en· W2116788334 on OpenAlexvenueno aff
Marcin Milchert, Katarzyna Fischer, Jacek Fliciński, Hanna Przepiera‐Będzak, Marek Brzosko

Bibliographic record

VenueThe Journal of Rheumatology · 2012
Typeletter
Languageen
FieldMedicine
TopicVasculitis and related conditions
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineGiant cell arteritisVasculitisArteritisArteriosclerosisThickeningVascular diseaseRadiologyPathologyDiseaseCardiologySurgery

Abstract

fetched live from OpenAlex

To the Editor: We followed with great interest the report by Czihal, et al 1 presenting new possibilities of objective, noninvasive diagnostic procedures that remain insufficient in giant cell arteritis (GCA). We would like to share our clinical experiences with arteritic changes in patients with GCA. Sonographic presentations of vasculitis may be mistaken for arteriosclerosis, especially in elderly patients who typically have GCA. That was the case in a patient with mild systemic manifestations and insidious disease onset. A 64-year-old woman presented with carotidynia — a rare manifestation of GCA. Color duplex sonography (CDS) revealed hypoechoic, homogenous, circumferential but not symmetrical bilateral wall thickening involving carotid and internal carotid arteries up to 15 mm from the carotid … Address correspondence to Dr. Milchert; E-mail: marcmilc{at}hotmail.com

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)0.002
metaresearch head score (Gemma)0.013
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: Commentary · Consensus signal: Commentary
Teacher disagreement score0.016
Threshold uncertainty score0.012

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.013
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0010.001
Science and technology studies0.0010.002
Scholarly communication0.0020.003
Open science0.0020.001
Research integrity0.0160.008
Insufficient payload (model declined to judge)0.0040.002

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 head0.017
GPT teacher head0.236
Teacher spread0.219 · 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
GenreCommentary

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

Citations6
Published2012
Admission routes1
Has abstractyes

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