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Evolution of the Coronary Artery Stent

2011· article· en· W2010174007 on OpenAlexaff
Rahul Nayak

Bibliographic record

VenueJournal of Long-Term Effects of Medical Implants · 2011
Typearticle
Languageen
FieldMedicine
TopicCoronary Interventions and Diagnostics
Canadian institutionsQueen's University
Fundersnot available
KeywordsMedicineStentCoronary artery diseaseLeft main coronary artery diseaseIncidence (geometry)Psychological interventionArteryCardiologyIntensive care medicineInternal medicineSurgeryBypass grafting

Abstract

fetched live from OpenAlex

"Necessity, who is the mother of invention." - Plato. There has been a steady rise in the incidence and prevalence of coronary artery disease. In most developed countries, it is the number one cause of morbidity and mortality. As this disease has become an ever increasing burden on society, it has spurred on the development of many radical and innovative procedures and implants. This paper will discuss, briefly, the history of coronary interventions ranging from coronary artery bypass grafts (CABG) to drug-eluting stents. It will then compare and contrast some of the several drug-eluting stents available on the market today; specifically focusing on the Cypher™, Taxus™, Endeavour™, and Xience VTM stents. The comparisons will include a basic overview of the specifications of each stent as well as the short- and long-term outcomes of these implants. Finally, the paper will provide an introduction to some of the latest stent technology awaiting FDA approval.

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)0.004
metaresearch head score (Gemma)0.006
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.004
Threshold uncertainty score0.024

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.006
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0020.001
Science and technology studies0.0010.003
Scholarly communication0.0030.004
Open science0.0010.002
Research integrity0.0030.006
Insufficient payload (model declined to judge)0.0030.002

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 head0.024
GPT teacher head0.295
Teacher spread0.271 · 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 designNot applicable
Domainnot available
GenreReview

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

Citations0
Published2011
Admission routes1
Has abstractyes

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