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Record W4410543846 · doi:10.1177/15443167251319067

Upper Extremity Arterial Aneurysms: Correlation of Clinical, Ultrasound, and Operative Findings

2025· article· en· W4410543846 on OpenAlexaff
D. Williams, Elizabeth M. Wooster, Charles E. Stonerock, Douglas L. Wooster

Bibliographic record

VenueJournal for Vascular Ultrasound · 2025
Typearticle
Languageen
FieldMedicine
TopicVascular Procedures and Complications
Canadian institutionsToronto Metropolitan UniversityUniversity of Toronto
Fundersnot available
KeywordsMedicineUltrasoundRadiologyAneurysmPulsatile flowDuplex (building)Modality (human–computer interaction)Arterial wallIntervention (counseling)SurgeryCardiologyComputer scienceArtificial intelligence

Abstract

fetched live from OpenAlex

Upper extremity arterial aneurysm is an unusual finding, characterized by a pulsatile mass and sometimes complicated by embolism or rupture. Color duplex is the definitive imaging modality to identify, measure, and demonstrate the aneurysm’s relationship to adjacent structures. Ultrasound data are used in part to determine management options and to conduct post-intervention surveillance. A review of archived “teaching files” was undertaken to locate patients with upper extremity arterial aneurysms. Data related to initial ultrasound findings, intervention planning, operative procedures, and surveillance were gathered. A focused literature search was conducted to support the collated material. Identifying patient information was culled from each case dataset.

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)0.003
metaresearch head score (Gemma)0.012
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.006
Threshold uncertainty score0.014

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.012
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0060.003
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0000.000
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 head0.024
GPT teacher head0.361
Teacher spread0.337 · 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 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

Citations0
Published2025
Admission routes1
Has abstractyes

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