Deformable Mock Stenotic Artery With a Lipid Pool
Bibliographic record
Abstract
The comparison, evaluation, and optimization of new techniques, models, or algorithms often require the use of realistic deformable test phantoms. The purpose of this paper is to present a multilayer deformable test specimen mimicking an atherosclerotic coronary artery, suitable for mechanical testing and intravascular imaging. Mock arteries were constructed in three phases using two molds: building a first layer of polyvinyl alcohol (PVA) cryogel, adding a lipid pool and building a second layer of PVA cryogel. To illustrate the deformation of the mock arteries, one has been placed in a custom-made bath, axially stretched then inflated while acquiring intravascular ultrasound (IVUS) images. The resulting specimen presents a progressing lumen narrowing of 25% in cross-sectional area at the peak and a lipid pool. The average inner gel layer is about 0.4 mm thick and the outer about 0.6 mm. The dimensions are of the same order as clinical observations, the first gel layer mimicking the intima-media and the second layer the adventitia. In the sequence of IVUS images, the different components of the mock artery are visible and differentiable. The variation in diameter of the segmented contours is presented for a specific specimen subjected to intraluminal pressure. This double-layer stenotic mock artery is approximately the size of a human coronary artery, has a lipid inclusion, can withstand relative large deformation, suitable for (intravascular) ultrasound imaging, and has customizable geometry and wall material parameters.
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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
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".