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Insuffisance tricuspide en 2023 : modalités de traitement pour la valve oubliée

2023· article· fr· W4323533742 on OpenAlexaff
David Meier, Mariama Akodad, Γεώργιος Τζίμας, Fabien Doguet, Julius Jelisejevas, Robert Boone, Janarthanan Sathananthan, Philipp Blanke, Jonathon Leipsic, Olivier Müller, John G. Webb, Fabien Praz

Bibliographic record

VenueRevue Médicale Suisse · 2023
Typearticle
Languagefr
FieldMedicine
TopicCardiac Valve Diseases and Treatments
Canadian institutionsSt. Paul's Hospital
Fundersnot available
KeywordsMedicinePercutaneousGynecologyVentricleRegurgitation (circulation)SurgeryCardiology

Abstract

fetched live from OpenAlex

The negative impact of tricuspid regurgitation on prognosis in now well established. It also appears clear that surgical and possibly percutaneous treatment should be performed before reaching a point of no return with advanced heart failure and deterioration of right ventricle function. Percutaneous treatment has been divided into coaptation restoration devices, annuloplasty devices, and ortho- or heterotopic valve replacement. The present article offers a brief review of diagnostic modalities beyond echocardiography, surgical treatment as well as of the multiple recent development in the percutaneous treatment of this frequent condition.

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: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.002
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.001

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 head0.027
GPT teacher head0.362
Teacher spread0.335 · 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
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

Citations1
Published2023
Admission routes1
Has abstractyes

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