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Record W4391172613 · doi:10.3389/fmedt.2024.1320810

The left ventricular outflow tract and carotid artery velocity time integrals

2024· article· en· W4391172613 on OpenAlexaff
Jon‐Émile S. Kenny

Bibliographic record

VenueFrontiers in Medical Technology · 2024
Typearticle
Languageen
FieldMedicine
TopicHemodynamic Monitoring and Therapy
Canadian institutionsHealth Sciences North
Fundersnot available
KeywordsVentricular outflow tractOutflowVentricleCardiologyPeripheralInflowInternal medicineMedicineDoppler effectArteryStroke volumeMechanicsGeologyPhysicsHeart failure

Abstract

fetched live from OpenAlex

The left ventricular outflow tract velocity time integral (LVOT VTI) is commonly used in the intensive care unit as a measure of stroke volume (SV) and how the SV changes in response to an intervention; therefore, the LVOT VTI is used to guide intravenous fluid management. Various peripheral Doppler surrogates are proposed to infer the LVOT VTI (e.g., measures from the common carotid artery). A recently-described, novel method of insonation has an excellent ability to detect change in the LVOT VTI. This approach raises important facets of Doppler flow and insonation error, as well as the general principles at play when using a peripheral artery to infer changes from the left ventricle. Relating the VTI of a peripheral artery to the LVOT VTI was recently described mathematically and may help clinicians think about the Doppler relationship between central and peripheral flow.

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)0.001
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: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.881
Threshold uncertainty score0.435

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.005
GPT teacher head0.254
Teacher spread0.250 · 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 designOther design
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

Citations4
Published2024
Admission routes1
Has abstractyes

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