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Record W3045498028 · doi:10.3791/61251

A Novel Right Ventricular Volume and Pressure Loaded Piglet Heart Model for the Study of Tricuspid Valve Function.

2020· article· en· W3045498028 on OpenAlexaff
Lily Lin, Sanaz Hatami, James Y. Coe, Timothy Colen, Consolato Sergi, Richard B. Thompson, Elena S. Di Martino, Walter Herzog, Ziad Abu Sara, Darren H. Freed, Nee Scze Khoo

Bibliographic record

VenueJournal of Visualized Experiments · 2020
Typearticle
Languageen
FieldMedicine
TopicCardiac Valve Diseases and Treatments
Canadian institutionsUniversity of CalgaryUniversity of Alberta
Fundersnot available
KeywordsVentricleCardiologyMedicineIntracardiac injectionInternal medicineTricuspid valvePulmonary arteryHeart failurePulmonary artery bandingAnimal modelVentricular pressureHemodynamics

Abstract

fetched live from OpenAlex

Heart conditions in which the tricuspid valve (TV) faces either increased volume or pressure stressors are associated with premature valve failure. Mechanistic studies to improve our understanding of the underlying pathophysiology responsible for the development of premature TV failure are lacking. Due to the inability to conduct these studies in humans, an animal model is required. In this manuscript, we describe the protocols for a novel chronic recovery infant piglet heart model for the study of changes in the TV when placed under combined volume and pressure stress. In this model, volume loading of the right ventricle and the TV is achieved through the disruption of the pulmonary valve. Then pressure loading is accomplished through the placement of a pulmonary artery band. The success of this model is assessed at four weeks post intervention surgery through echocardiography, intracardiac pressure measurement, and pathologic examination of the heart specimens.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.202
Threshold uncertainty score0.406

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
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 head0.042
GPT teacher head0.417
Teacher spread0.375 · 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
Published2020
Admission routes1
Has abstractyes

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