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Record W4410122459 · doi:10.24908/pocusj.v10i01.18498

A Point of Care Ultrasound (POCUS) Artifact Mimicking an Aortic Dissection: A Case Series

2025· article· en· W4410122459 on OpenAlexvenueno aff
Olivia Klee, Julia Buechler, Molly Fears, Caroline Gosser, Kahra Nix

Bibliographic record

VenuePOCUS Journal · 2025
Typearticle
Languageen
FieldMedicine
TopicUltrasound in Clinical Applications
Canadian institutionsnot available
Fundersnot available
KeywordsArtifact (error)Sagittal planeMedicineAbdominal aortaUltrasoundAortaRadiologySurgeryComputer scienceComputer vision

Abstract

fetched live from OpenAlex

Introduction: This case series describes a point of care ultrasound (POCUS) artifact involving the abdominal aorta of four standardized patients. The purpose of this case series is to highlight this artifact and maneuvers to discern pathology from normal. Methods: Permission was obtained for each case described in this series. POCUS images of the abdominal aorta in both sagittal and transverse were obtained in these four cases. The findings were reviewed and compared. Discussion: All four standardized patients were otherwise healthy, thin and female. The artifact was consistently a linear, hyperechoic structure within the lumen of the abdominal aorta in the sagittal plane. Conclusion: In each of these cases, the artifact disappeared on rotation of the probe from the sagittal plane to the transverse plane. Knowledge of this POCUS artifact and maneuvers to avoid it are important in both clinical and educational settings.

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)0.007
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.004
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.007
Meta-epidemiology (narrow)0.0030.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.002
Science and technology studies0.0020.002
Scholarly communication0.0020.002
Open science0.0010.002
Research integrity0.0040.002
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 head0.023
GPT teacher head0.361
Teacher spread0.338 · 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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