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Record W2099971543 · doi:10.1186/1532-429x-11-s1-o91

Spatiotemporal relationship between ventricular expansion and flow propagation during early filling

2009· article· en· W2099971543 on OpenAlexaff
Thompson Richard, June Cheng Baron, Kelvin Chow, Jessica M. Scott, Ben T. Esch, Mark J. Haykowsky, Ian C. Paterson

Bibliographic record

VenueJournal of Cardiovascular Magnetic Resonance · 2009
Typearticle
Languageen
FieldMedicine
TopicCardiovascular Function and Risk Factors
Canadian institutionsUniversity of British ColumbiaUniversity of Alberta
Fundersnot available
KeywordsPreloadBlood flowVentricleMedicineCardiologyDiastoleAngiologyInternal medicineFlow (mathematics)MechanicsRelaxation (psychology)Flow velocityHemodynamicsPhysicsBlood pressure

Abstract

fetched live from OpenAlex

Flow propagation refers to the delay in the onset of blood flow during early filling at more apical ventricular locations. The velocity of flow propagation (V p ) into the left ventricle (LV) provides a preload insensitive estimate of LV relaxation, confirmed invasively by a strong negative correlation with the relaxation time constant (tau) [ 1 , 2 ]. Clinically, V p < 50 ms is commonly taken as evidence of abnormal diastolic function. No direct physical relationship between muscle relaxation and flow propagation has been previously illustrated. By simultaneous measurement of myocardial mechanics (radial expansion) and blood patterns throughout the LV and during early filling we expect to illustrate a correlated spatial and temporal relationship between the mechanics which drive blood flow and the resulting blood flow patterns.

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)0.000
metaresearch head score (Gemma)0.001
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: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
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 integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.015
GPT teacher head0.228
Teacher spread0.213 · 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
Published2009
Admission routes1
Has abstractyes

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