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Record W19606927 · doi:10.1177/159101991301900408

Y-Crossing of Braided Stents with Stents and Flow Diverters Does Not Cause Significant Stenosis in Bench-Top Studies

2013· article· en· W19606927 on OpenAlexaff
Alina Makoyeva, Tim E. Darsaut, Igor Salazkin, Jean Raymond

Bibliographic record

VenueInterventional Neuroradiology · 2013
Typearticle
Languageen
FieldMedicine
TopicIntracranial Aneurysms: Treatment and Complications
Canadian institutionsUniversity of AlbertaUniversité de MontréalHôpital Notre-Dame
Fundersnot available
KeywordsStentStenosisMedicineFlow diverterBifurcationRadiologyAneurysmPhysics

Abstract

fetched live from OpenAlex

Y-stent placement to treat bifurcation aneurysms requires the second device to cross the confines of the first stent, with concerns regarding the formation of stenosis of the second device at the site of crossing. Various braided stents and flow diverters (FDs) were deployed to cross through a high porosity braided stent, in a Y configuration, with the ends of the devices inserted in plastic tubes of various diameters, leaving the mid-portion free to expand. The ensuing constructs were photographed, paying attention to the degree of stenosis, if any, created where the second device crosses the first stent. Experiments were repeated selecting different zones of the first stent as the site of crossing for the second device, different tube diameters, and changing the angle of the bifurcation. Crossing the first stent did not cause the second stent to become significantly stenosed in any case. Crossing through the transition or expansion zone of the first device had no influence on results. Different bifurcation angles had no influence on the occurrence of stenosis. Y-stent placement to treat arterial bifurcations using braided self-expanding stents and FDs does not lead to significant stenosis in bench-top studies.

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 imitation

Not 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.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.043
GPT teacher head0.298
Teacher spread0.255 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
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

Citations7
Published2013
Admission routes1
Has abstractyes

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