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Record W2068433958 · doi:10.1002/clc.4960121310

New perspectives on left ventricular hypertrophy: Anatomy, physiology, and significance

2009· article· en· W2068433958 on OpenAlexaff
Henk E.D.J. ter Keurs, Daniel D. Savage, Wanda M. Lester, D L McGee

Bibliographic record

VenueClinical Cardiology · 2009
Typearticle
Languageen
FieldMedicine
TopicCardiovascular Function and Risk Factors
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsLeft ventricular hypertrophyMedicineMuscle hypertrophyInternal medicineCardiologyOverweightPopulationAfterloadHeredityBlood pressureHemodynamicsBody mass index

Abstract

fetched live from OpenAlex

The advent of echocardiography has added an important and sensitive tool for assessment of left ventricular hypertrophy (increased left ventricular mass). Recent echocardiographic studies in large population-based samples suggest an epidemic of left ventricular hypertrophy. Preliminary data suggesting important prognostic importance for such left ventricular hypertrophy (independent of standard risk factors) has fueled interest in the development, determinants, and other features of the hypertrophy. Hemodynamic and neurohumoral factors are the most prominent stimuli to adaptive (physiologic) myocardial hypertrophy, which can progress to maladaptive (pathologic) hypertrophy. The overall blood pressure experience, overweight, the cardiovascular response to recurrent psychosocial stress and physical activity level are four important correlates and potential determinants of left ventricular mass in various urban-suburban populations. Determination of the relative contributions and interrelations of these and other factors (such as heredity) to various forms of left ventricular hypertrophy found in various demographic groups warrants intensive investigation.

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)0.004
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.005
Threshold uncertainty score0.023

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.003
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0030.002
Science and technology studies0.0000.007
Scholarly communication0.0020.006
Open science0.0010.001
Research integrity0.0020.004
Insufficient payload (model declined to judge)0.0050.001

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 head0.025
GPT teacher head0.331
Teacher spread0.306 · 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 designNot applicable
Domainnot available
GenreReview

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

Citations9
Published2009
Admission routes1
Has abstractyes

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