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Record W4387064051 · doi:10.1097/hco.0000000000001083

Designing the coronary artery bypass surgery operation of the future

2023· article· en· W4387064051 on OpenAlexaff
Marc Ruel

Bibliographic record

VenueCurrent Opinion in Cardiology · 2023
Typearticle
Languageen
FieldMedicine
TopicCardiac and Coronary Surgery Techniques
Canadian institutionsUniversity of Ottawa
Fundersnot available
KeywordsMedicineCardiopulmonary bypassBypass graftingArteryCoronary artery diseaseCoronary artery bypass surgeryBypass surgeryCardiologyGuidelineSurgeryInternal medicine

Abstract

fetched live from OpenAlex

PURPOSE OF REVIEW: This article discusses current shortcomings in coronary artery bypass surgery and ways to overcome them. RECENT FINDINGS: Minimally invasive coronary bypass surgery, robotic coronary bypass, and hybrid approaches aim to avoid sternotomy, employ arterial grafts, and minimize the use of cardiopulmonary bypass. Other considerations such as bypass graft validation, the optimization of guideline-directed medical therapy, and the development of coronary surgery specialists are also crucial to further the benefits of coronary artery bypass grafting on future patients. SUMMARY: Coronary artery bypass grafting must become less invasive, be better validated, and be carried out with an even higher emphasis on quality, including graft validation and preoperative/postoperative optimization, if it is to remain the best treatment for advanced, severe coronary artery disease.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.082
Threshold uncertainty score0.277

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
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 head0.055
GPT teacher head0.326
Teacher spread0.271 · 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.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations2
Published2023
Admission routes1
Has abstractyes

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