MétaCan
Menu
Back to cohort
Record W2122258678 · doi:10.4021/cr101w

Giant Aortic Arch Aneurysm and Cardio-vocal Syndrome: Still an Open-surgery Indication

2011· article· en· W2122258678 on OpenAlexvenueno aff
Jose M Garrido

Bibliographic record

VenueCardiology Research · 2011
Typearticle
Languageen
FieldMedicine
TopicAortic Disease and Treatment Approaches
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineCardiologyPresentation (obstetrics)Internal medicineAortic archAneurysmAortic aneurysmPalsyOpen surgerySurgeryAortaPathology

Abstract

fetched live from OpenAlex

The Cardio-vocal Syndrome (Ortner's syndrome) is described as hoarseness due to the left recurrent laryngeal nerve palsy, caused by a specific cardiovascular pathology. In this case, we present a patient with a giant aortic arch aneurysm with an initial clinical presentation of Cardio-vocal Syndrome. The conventional open-surgery, instead of endovascular approach, was useful to control the morbidity from the compressive effect of adjacent structures, also preventing the aortic rupture. We strongly recommend analyzing carefully the individual case and the clinical targets to resolve, because the new technologies are not always the most effective therapeutic response.

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)0.003
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 score0.005
Threshold uncertainty score0.015

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.003
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 integrity0.0040.002
Insufficient payload (model declined to judge)0.0050.000

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 head0.278
GPT teacher head0.402
Teacher spread0.124 · 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

Citations4
Published2011
Admission routes1
Has abstractyes

Explore more

Same venueCardiology ResearchSame topicAortic Disease and Treatment ApproachesFrench-language works237,207