Bibliographic record
Abstract
Although ultrasound imaging is an important technique, technical improvements are needed before its full potential is realized and for diagnosis and management of vascular disease and visualizing small vessels. The authors believe that 2-D viewing of 3-D anatomy, using the conventional ultrasound procedures, limits one's ability to quantify and visualize vascular diseases. The authors' goal is to develop a 3-D ultrasound technique for imaging the vasculature using B-mode, colour Doppler, and Doppler power. In their approach, the ultrasound probe is connected to an assembly that translates or rotates the probe rapidly, while 2-D ultrasound images are digitized. The sequence of 2-D images are reconstructed into a 3-D image, which can be manipulated interactively. The authors have shown that 3-D imaging with B-mode, colour Doppler and Doppler power can be useful in assessing atherosclerosis, imaging of the kidney and spleen, as well as imaging of angiogenic vessels. Specifically, in this paper the authors also show that imaging of the carotid arteries has demonstrated that the technique can be used for stenosis and plaque volume measurements, as well as for assessment of the complexity of the plaque.
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 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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.015 | 0.004 |
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".