A Content Analysis of the <i>Journal for Vascular Ultrasound</i> : Challenges and Opportunities
Bibliographic record
Abstract
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.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.055 | 0.151 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.031 | 0.043 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.007 | 0.005 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".