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Record W2003891817 · doi:10.1177/1089253210371522

Aortic Atheroma and Adverse Cerebral Outcome: Risk, Diagnosis, and Management Options

2010· article· en· W2003891817 on OpenAlex
Hilary P. Grocott, Tony Tran

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueSeminars in Cardiothoracic and Vascular Anesthesia · 2010
Typearticle
Languageen
FieldMedicine
TopicAortic aneurysm repair treatments
Canadian institutionsUniversity of Manitoba
Fundersnot available
KeywordsMedicinePerioperativeAtheromaAscending aortaCardiac surgeryRadiologyDiseaseCardiologyAdverse effectAortaInternal medicineSurgery

Abstract

fetched live from OpenAlex

Aortic atheromatous disease is a common finding in the patient presenting for cardiac surgery. Adverse neurologic outcome has been closely linked to the extent of aortic atherosclerosis. In order to optimize perioperative outcomes, the location and severity of disease needs accurate characterization using multimodal techniques. Although various preoperative radiographic techniques have variably identified patients with significant atheroma, intraoperative echocardiographic imaging has proven most useful in localizing and characterizing the degree of aortic atheroma. Epiaortic assessment of the ascending aorta has been utilized in guiding surgical modifications and interventions aimed at reducing the risk of neurologic injury. Although no particular technique has been definitely studied, avoidance of the identifiable atheromatous aortic region has been a main feature of the various modifications employed to optimize neurologic outcome after cardiac surgery.

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.

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 score0.027
Threshold uncertainty score0.947

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 head0.010
GPT teacher head0.283
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