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FUNCTIONAL CHARACTERISTICS OF BIOLOGICAL PROTECTION «UNILINE»

2017· article· en· W2756873436 on OpenAlexaboutno aff
K. Yu. Klyshnikov, Е. А. Овчаренко, N. A. Scheglova, Л. С. Барбараш

Bibliographic record

VenueComplex Issues of Cardiovascular Diseases · 2017
Typearticle
Languageen
FieldMedicine
TopicCardiovascular Issues in Pregnancy
Canadian institutionsnot available
Fundersnot available
KeywordsBody orificeBiomedical engineeringRegurgitation (circulation)Heart valveAortic valvePressure gradientMaterials scienceVolume (thermodynamics)CardiologyMechanical engineeringMedicineMechanicsEngineeringPhysics

Abstract

fetched live from OpenAlex

The aim of the work was to evaluate the hydrodynamic characteristics of the heart valve bioprosthesis «UniLine», intended for prosthetics of the aortic valve. Materials and methods . In the contest three prostheses «UniLine» with a size of 21, 23, 25 mm, intended for clinical use. The evaluation of the hydrodynamic parameters was carried out in a Vivitro pulsating flow setup (Vivitro Labs, Canada) simulating the operation of the «left» half of the heart. Estimated hydrodynamic function of all prostheses when creating the physiological mode of operation of the unit - impact volume = 70 ml, minute volume = 5 l/min, mean aortic pressure = 100 mmHg. Results . The average trans-prosthetic gradient was 5,4-15,5 mmHg.; the maximum trans-prosthetic gradient was 11,9-25,2 mmHg; effective orifice area 1,38-2,15 cm2; regurgitation fraction 1,5-3,905%; productivity index, calculated from the inner orifice diameter 47,4-68,5%. Conclusion . Bioprostheses «UniLine», intended for aortic position, demonstrated satisfactory hydrodynamic in vitro characteristics, comparable with existing world analogues. The existing design has the potential to increase hydrodynamic efficiency, but requires advanced approaches and methods, such as FSI, for its implementation.

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 imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.654
Threshold uncertainty score0.909

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.003
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.076
GPT teacher head0.305
Teacher spread0.229 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
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

Citations3
Published2017
Admission routes1
Has abstractyes

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