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La tricuspide: la valve que l’on ne peut plus oublier

2025· article· fr· W4410545979 on OpenAlexaff
Sarah Mauler‐Wittwer, George Giannakopoulos, Marc Arcens, Damien Guijaro, Nana K. Poku, Philippe Meyer, Hajo Müller, Stéphane Noble

Bibliographic record

VenueRevue Médicale Suisse · 2025
Typearticle
Languagefr
FieldMedicine
TopicCardiac Valve Diseases and Treatments
Canadian institutionsInstitut Universitaire de Gériatrie de Montréal
Fundersnot available
KeywordsGeology

Abstract

fetched live from OpenAlex

The prevalence of tricuspid regurgitation (TR) increases with age and female sex. Ventricular dysfunction, splanchnic overload, renal failure, and liver congestion contribute to its morbi-mortality. The most common etiology of TR is secondary to right atrial or ventricular dilatation. The TRI-SCORE, a risk score assessing the intrahospital mortality of isolated TR surgery, should be available in the heart team discussion. Surgical valve repair improves survival with low or intermediate TRI-SCORE, but not with high TRI-SCORE. Transcatheter repair and replacement showed TR reduction and improved life quality scores, but without differences in death or heart failure hospitalizations. TR intervention should be performed before the disease is too advanced (low or intermediate TRI-SCORE).

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)0.004
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 score0.007
Threshold uncertainty score0.022

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0010.003
Scholarly communication0.0030.003
Open science0.0000.001
Research integrity0.0030.003
Insufficient payload (model declined to judge)0.0070.003

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 head0.021
GPT teacher head0.372
Teacher spread0.352 · 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

Citations1
Published2025
Admission routes1
Has abstractyes

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