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Record W2981251952 · doi:10.1177/1544316719874570

A Content Analysis of the <i>Journal for Vascular Ultrasound</i> : Challenges and Opportunities

2019· article· en· W2981251952 on OpenAlexaff
Douglas L. Wooster, Mary E. Angelson, David Williams

Bibliographic record

VenueJournal for Vascular Ultrasound · 2019
Typearticle
Languageen
FieldMedicine
TopicAortic aneurysm repair treatments
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsUltrasoundMedicineRadiology

Abstract

fetched live from OpenAlex

The Quality Improvement and Research Committee of the Society for Vascular Ultrasound has recognized the Journal for Vascular Ultrasound to promote quality improvement, research and scholarly initiatives of the Society. An understanding of the content and character of its published articles and its status amongst journals on vascular ultrasound will be useful to this mandate. This project aims to identify the scope of Journal for Vascular Ultrasound and its implications for the Society membership. Journal for Vascular Ultrasound Volumes 40 to 42 (2016-2018) were reviewed to identify the number of articles published, the type of scholarly work, and the vascular ultrasound domains represented. The findings were compared with major databases and a targeted list of journals with vascular ultrasound content. In addition, bibliometric parameters specific to Journal for Vascular Ultrasound were identified and compared with other journals. The Journal for Vascular Ultrasound published 71 articles over the 3 years; 100% were vascular ultrasound topics. The most frequent activities were 35 cases, 20 research, and 5 guidelines. The topics were 19 venous, 18 carotid, 7 arterial, 2 aorta, 1 education, and 10 unusual findings, and 4 other studies. In the 312 targeted journals, 4792 articles were published in 2018; 135 were relevant to vascular ultrasound. The maximum vascular ultrasound content in any one journal, other than Journal for Vascular Ultrasound, was 20% (range = 0-20, median = 8%). The impact of Journal for Vascular Ultrasound, by the H-score of 11 and SJR of 0.12, ranks the Journal for Vascular Ultrasound in the lowest 10% of surveyed journals. Of the citable Journal for Vascular Ultrasound articles, only 6% were cited in bibliometric analysis. The Journal for Vascular Ultrasound has the highest percentage of content of vascular ultrasound of targeted journals. Case reports represent the bulk of Journal for Vascular Ultrasound published work. Citations and impact remain low. None of the targeted journals have very much content in vascular ultrasound. These findings suggest a variety of challenges and opportunities for the Society.

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 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)0.002
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation 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 score0.186
Threshold uncertainty score0.836

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.002
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.076
GPT teacher head0.293
Teacher spread0.217 · 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 teacher head, 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

Citations1
Published2019
Admission routes1
Has abstractyes

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