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Record W2965911722 · doi:10.3389/fcvm.2019.00122

Percutaneous Mitral Edge-to-Edge Repair: State of the Art and a Glimpse to the Future

2019· review· en· W2965911722 on OpenAlexaff
Faisal Khan, Mirjam Winkel, Géraldine Ong, Nicolas Brugger, Thomas Pilgrim, Stephan Windecker, Fabien Praz, Neil Fam

Bibliographic record

VenueFrontiers in Cardiovascular Medicine · 2019
Typereview
Languageen
FieldMedicine
TopicCardiac Valve Diseases and Treatments
Canadian institutionsSt. Michael's HospitalUniversity of Toronto
Fundersnot available
KeywordsPercutaneousMedicineEnhanced Data Rates for GSM EvolutionCardiologyInternal medicineComputer scienceArtificial intelligence

Abstract

fetched live from OpenAlex

Patients with severe symptomatic mitral regurgitation have a poor prognosis if left untreated. In those patients who are not eligible for mitral valve surgery, percutaneous edge-to-edge repair may improve clinical outcomes. Recent clinical trials have added to our knowledge and provide interesting insights into the management of such patients. With an increasingly aging global population, these technologies are likely to represent an important treatment option. This mini-review will examine the technology, the evidence and the latest developments in percutaneous mitral edge-to-edge repair.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.876
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0050.010
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.013
GPT teacher head0.299
Teacher spread0.286 · 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 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

Citations23
Published2019
Admission routes1
Has abstractyes

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