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Record W2592660893 · doi:10.22489/cinc.2016.055-149

The Pressure Gradient across the Endocardium

2016· article· en· W2592660893 on OpenAlexaff
Rachad M. Shoucri

Bibliographic record

VenueComputing in cardiology · 2016
Typearticle
Languageen
FieldMedicine
TopicCardiovascular Function and Risk Factors
Canadian institutionsRoyal Military College of Canada
Fundersnot available
KeywordsEndocardiumPressure gradientComputer scienceCardiologyPhysicsMechanicsMedicine

Abstract

fetched live from OpenAlex

A mathematical formalism for the non-linear endsystolic pressure-volume relation (ESPVR) in the heart ventricles has the interesting feature that the peak active pressure generated by the myocardium (also called peak isovolumic pressure Pisom by physiologists) is included in the mathematical formalism describing the ESPVR.In this study we look at the ratio (Pisom -Pm)/Pm as an index to segregate between different clinical groups, this ratio can be calculated in a non-invasive way with the mathematical model used.Application to the left ventricle by using clinical data taken from the medical literature is given and discussed.Mathematical relations between the ejection fraction (EF) and the parameters describing the ESPVR are used in a way to get new insight into the problem of heart failure with normal or preserved ejection fraction (HFpEF).

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)0.001
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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.003
Threshold uncertainty score0.010

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0020.002
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.001

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 head0.015
GPT teacher head0.279
Teacher spread0.264 · 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 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

Citations0
Published2016
Admission routes1
Has abstractyes

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