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Record W2755974114 · doi:10.1055/s-0037-1604299

New Treatment Approaches to Arteriovenous Malformations

2017· review· en· W2755974114 on OpenAlex
Patrick Gilbert, Josée Dubois, M.F. Giroux, Gilles Soulez

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 Interventional Radiology · 2017
Typereview
Languageen
FieldMedicine
TopicVascular Malformations Diagnosis and Treatment
Canadian institutionsUniversité de MontréalCentre Hospitalier Universitaire Sainte-JustineCentre Hospitalier de l’Université de Montréal
Fundersnot available
KeywordsMedicineArteriovenous malformationRadiologyIntensive care medicine

Abstract

fetched live from OpenAlex

Arteriovenous malformations (AVMs) are high-flow vascular anomalies that have demonstrated a very high recurrence rate after endovascular treatment, surgical treatment, or a combination of both. Surgical treatments have shown good response when they are small and well localized but a poor response when diffuse. A better understanding of the nature of the lesion has led to a better response rate and a safer treatment for these patients. This has been accomplished through a detailed understanding of the angioarchitecture of the lesion, enabling a tailored approach in reaching and targeting the nidus of the AVM with different liquid embolic agents, more specifically ethanol. Flow reduction techniques help in exposing the nidus to sclerosant agents. A clinical classification, the Schobinger classification, will help determine the appropriate time to start or to pursue therapy.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.990
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.001

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 head0.343
GPT teacher head0.412
Teacher spread0.069 · 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