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Record W3135413231 · doi:10.1016/j.xjtc.2021.02.032

Commentary: Getting to the art of the matter with aortic valve repair

2021· editorial· en· W3135413231 on OpenAlexaboutno aff
John M. Trahanas, Edward P. Chen

Bibliographic record

VenueJTCVS Techniques · 2021
Typeeditorial
Languageen
FieldMedicine
TopicCardiac Valve Diseases and Treatments
Canadian institutionsnot available
Fundersnot available
KeywordsRegurgitation (circulation)Aortic valveMedicineCardiologyInternal medicineAortic valve replacementAortic rootAortic valve repairSurgeryAorta

Abstract

fetched live from OpenAlex

Surgical aortic valve replacement for aortic regurgitation using either a mechanical or bioprosthetic prosthesis is suboptimal due to the potential for structural degeneration and need for reoperation or the inherent risks of anticoagulation.1 Aortic valve repair represents an attractive alternative that preserves native valve function. However, owing to alterations to aortic root geometry and the aortic cusps that may be needed to achieve valve competency, this procedure is complex. The specific components of the valve and root apparatus to target for intervention often can be difficult to determine.

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)0.006
metaresearch head score (Gemma)0.055
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: Not applicable
GenreCandidate signal: Editorial · Consensus signal: none
Teacher disagreement score0.052
Threshold uncertainty score0.066

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.055
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0020.002
Bibliometrics0.0010.001
Science and technology studies0.0040.005
Scholarly communication0.0040.008
Open science0.0050.002
Research integrity0.0520.058
Insufficient payload (model declined to judge)0.0200.013

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 head0.005
GPT teacher head0.311
Teacher spread0.306 · 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
GenreEditorial

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

Citations0
Published2021
Admission routes1
Has abstractyes

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