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Record W2070556206 · doi:10.1510/mmcts.2008.003806

Repair of aortic valve cusp prolapse

2009· article· en· W2070556206 on OpenAlexaff
Munir Boodhwani, Laurent de Kerchove, David Glineur, Philippe Noirhomme, Gébrine El Khoury

Bibliographic record

VenueMultimedia Manual of Cardio-Thoracic Surgery · 2009
Typearticle
Languageen
FieldMedicine
TopicCardiac Valve Diseases and Treatments
Canadian institutionsUniversity of Ottawa
Fundersnot available
KeywordsMedicineCusp (singularity)Aortic valveAortic valve replacementAortic valve repairMargin (machine learning)CardiologyAortic Valve InsufficiencyInternal medicineSurgeryStenosisAortaAortic root

Abstract

fetched live from OpenAlex

Aortic valve preservation and repair is emerging as a feasible and attractive alternative to aortic valve replacement in young patients with aortic valve insufficiency. Cusp pathology requiring repair is present in up to 50% of patients undergoing aortic valve repair or valve preserving surgery and may occur in isolation or in conjunction with ascending aortic disease. Diagnosis of cusp prolapse can usually be made on preoperative echocardiography and is confirmed on surgical inspection. Techniques available for the correction of cusp prolapse in a trileaflet aortic valve include free margin plication, and free-margin resuspension. These techniques can be used alone or in combination and both provide stable mid-term results. Choice of technique may, therefore, be tailored to the cusp pathology encountered.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.219
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.006
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)0.0000.000

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 head0.022
GPT teacher head0.356
Teacher spread0.334 · 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.

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

Citations10
Published2009
Admission routes1
Has abstractyes

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