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Record W4235300147 · doi:10.1504/ijbet.2021.115972

Experimental design for testing and analysis of z-type self-expanding endovascular stents

2021· article· en· W4235300147 on OpenAlexaff
Joel C. R. Scott, Darrel A. Doman, Clifton R. Johnston

Bibliographic record

VenueInternational Journal of Biomedical Engineering and Technology · 2021
Typearticle
Languageen
FieldMedicine
TopicCoronary Interventions and Diagnostics
Canadian institutionsDalhousie University
Fundersnot available
KeywordsStentRadial Force VariationReduction (mathematics)Materials scienceComputer scienceBiomedical engineeringMechanical engineeringSurgeryMedicineGeometryEngineeringMathematics

Abstract

fetched live from OpenAlex

Stent migration and endoleak are common failure mechanisms for endovascular repair. Both can be partially attributed to a lack in understanding of the mechanical properties of endovascular stents. An alternative radial extensometer and machine vision system have been developed to both raise the quality of published radial force data, as well as to create and present an option for economical stent testing. The apparatus has shown promise as an accurate, repeatable, and reliable system for stent evaluation. Previous results by Johnston et al. examining z-type endovascular stents have been verified. Results showed that smaller stent diameters exhibit higher radial force than larger diameter stents, contrary to the expected outcomes due to increasing drag on increasing diameter stents. Stent orientation has been shown to contribute up to 8.8% error in radial force introduced by non-symmetrical brazed joints. The presence of a stent cover is shown to have negligible impact on stent radial force data above 10% reduction in area.

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)0.007
metaresearch head score (Gemma)0.007
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: Methods · Consensus signal: none
Teacher disagreement score0.014
Threshold uncertainty score0.047

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0070.007
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0020.001
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0140.002

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 head0.020
GPT teacher head0.297
Teacher spread0.276 · 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
GenreMethods

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

Citations1
Published2021
Admission routes1
Has abstractyes

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