Intravascular and intracardiac stents used in congenital heart disease
Classification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Intravascular or intracardiac stenoses occur in many forms of congenital heart disease or after attempted surgical repair. Although balloon dilation is one option for management, restenosis can occur due to elastic recoil immediately after the procedure. To address to such stenotic lesions, many reports support implanting endovascular stents to provide a framework for vessel expansion. Both balloon-expandable fixed tubular mesh stainless steel devices, and self-expandable stents have had an extensive clinical application. In pediatric patients, stents are used for a variety of stenoses, such as systemic venous obstruction pathways (eg, Mustard, Fontan baffle, or bidirectional cavopulmonary connections), pulmonary artery, right ventricular to pulmonary conduits, aortic coarctation, the arterial duct, aorticopulmonary collaterals, or postoperative systemic to pulmonary shunts. Because of improvements in device profile, implantation rates have increased. Complications such as stent fracture, migration, aneurysm formation, and in-stent restenosis occur but only rarely. This latter event may be because of intimal hyperplasia and/or continued vessel (and patient) growth related to the stent diameter. As such, some instances require redilation to manage the acquired lesion. Stent application has importantly altered management algorithms in congenital heart disease.
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 imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it