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Intracranial Arteriovenous Malformations: Real-Time Auto-triggered Elliptic Centric-ordered 3D Gadolinium-enhanced MR Angiography—Initial Assessment

2001· article· en· W2048594527 on OpenAlexaff
Richard Farb, Caitlin McGregor, Jae K. Kim, Matthieu Laliberte, J. Andrew Derbyshire, Robert A. Willinsky, Perry W. Cooper, David G. Westman, Gordon Cheung, Michael L. Schwartz, Jeffrey A. Stainsby, Graham A. Wright

Bibliographic record

VenueRadiology · 2001
Typearticle
Languageen
FieldMedicine
TopicVascular Malformations Diagnosis and Treatment
Canadian institutionsToronto Western HospitalUniversity of TorontoUniversity Health Network
Fundersnot available
KeywordsMedicineDigital subtraction angiographyGadoliniumRadiologyAngiographyArteriovenous malformationMagnetic resonance angiographyMagnetic resonance imagingNuclear medicine

Abstract

fetched live from OpenAlex

Auto-triggered elliptic centric-ordered three-dimensional (3D) gadolinium-enhanced magnetic resonance (MR) angiography was compared with 3D multiple overlapping thin-slab acquisition time-of-flight (TOF) MR angiography in the evaluation of intracranial arteriovenous malformations (AVMs) in 10 patients. Intraarterial digital subtraction angiography (DSA) was the reference standard. Gadolinium-enhanced MR angiograms were found to be equivalent to DSA images in AVM component depiction in 70%--90% of cases and were consistently superior to TOF MR angiograms.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.662
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.001

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 head0.011
GPT teacher head0.284
Teacher spread0.272 · 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.

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

Citations82
Published2001
Admission routes1
Has abstractyes

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