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Record W2509452495 · doi:10.21037/jtd.2016.07.58

The evolution of mitral valve prolapse: insights from the Framingham Heart Study

2016· letter· en· W2509452495 on OpenAlexaff
Zhaozhuo Niu, Vincent Chan, Thierry Mesana, Marc Ruel

Bibliographic record

VenueJournal of Thoracic Disease · 2016
Typeletter
Languageen
FieldMedicine
TopicCardiac Valve Diseases and Treatments
Canadian institutionsUniversity of Ottawa
Fundersnot available
KeywordsMitral valve prolapseMedicineMitral regurgitationCardiologyMitral annulusFramingham Heart StudyChordae tendineaeInternal medicineMagnetic resonance imagingMitral valveRadiologyDiseaseCardiac magnetic resonance imagingFramingham Risk ScoreBlood pressureDiastole

Abstract

fetched live from OpenAlex

The Framingham Heart Study group has described the non-diagnostic variants may evolve into mitral valve prolapse over time. These non-diagnostic variants include minimal systolic displacement, and abnormal anterior coaptation which is measured on surface echocardiography. Computed tomography and cardiac magnetic resonance imaging are evolving and can assess the degree of mitral regurgitation (MR); imaging techniques aside, genetic and proteomic detection of mitral prolapse is also evolving. However, the genetic basis for mitral prolapse is complex and likely involves multiple genetic loci. The same is also true for work determining possible biomarkers associated with mitral prolapse. The present study may be useful in counseling patients with a family history of mitral prolapse. Registry data is therefore of paramount importance in providing unbiased insight into this common disease.

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)0.008
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: Observational
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.003
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.008
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0000.000
Research integrity0.0020.002
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 head0.013
GPT teacher head0.350
Teacher spread0.337 · 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
GenreOther

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

Citations26
Published2016
Admission routes1
Has abstractyes

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