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Record W2800901908 · doi:10.21037/acs.2018.03.14

Management of the difficult left subclavian artery during aortic arch repair

2018· article· en· W2800901908 on OpenAlexaff
Ali Hage, Olivia Ginty, Adam Power, Luc Dubois, François Dagenais, Jehangir J. Appoo, John Bozinovski, Michael Chu

Bibliographic record

VenueAnnals of Cardiothoracic Surgery · 2018
Typearticle
Languageen
FieldMedicine
TopicAortic Disease and Treatment Approaches
Canadian institutionsUniversity of British ColumbiaLibin Cardiovascular Institute of AlbertaUniversity of CalgaryRoyal Jubilee HospitalLawson Health Research InstituteWestern University
Fundersnot available
KeywordsMedicineAortic archLeft subclavian arteryStroke (engine)Subclavian steal syndromeAneurysmSubclavian arterySurgeryAortaCardiologyRadiology

Abstract

fetched live from OpenAlex

Management of the left subclavian artery (SCA) during aortic arch surgery is associated with several challenges, including preserving distal perfusion, achieving hemostasis and preventing posterior circulation stroke and spinal cord injury. The most common challenge remains its deep position in the chest, often exacerbated by posterior and apical displacement from an arch aneurysm. We discuss several management options consisting of pre-, intra- and post-operative strategies and their respective advantages, disadvantages and clinical outcomes. A clinical algorithm is proposed to help guide decision-making in managing the difficult left SCA during aortic arch 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 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)0.002
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: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.000
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0010.001

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 head0.057
GPT teacher head0.331
Teacher spread0.273 · 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

Citations36
Published2018
Admission routes1
Has abstractyes

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