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Record W2018169410 · doi:10.3171/2008.11.jns08982

Angiographic computed tomography with selective microcatheterization in delineating surgical anatomy in the case of a dural arteriovenous fistula

2009· article· en· W2018169410 on OpenAlexaff
Muneer Eesa, Pranshu Sharma, Alim P. Mitha, Garnette R. Sutherland, Mayank Goyal

Bibliographic record

VenueJournal of neurosurgery · 2009
Typearticle
Languageen
FieldMedicine
TopicVascular Malformations Diagnosis and Treatment
Canadian institutionsUniversity of CalgaryFoothills Medical Centre
Fundersnot available
KeywordsMedicineTentoriumRadiologyDigital subtraction angiographyArteriovenous fistulaAngiographyFistulaArteriovenous malformationCerebral angiographyComputed tomography angiography

Abstract

fetched live from OpenAlex

Intracranial dural arteriovenous fistulas (dAVFs) are commonly encountered in centers specializing in cerebrovascular diseases. Knowing the precise site of fistulous communication with the venous structures is essential in targeting the appropriate surgical or endovascular therapy once a decision to treat has been made. Such sites can usually be located with digital subtraction angiography alone. The authors describe a case in which localization was best performed using cone-beam volume CT in the angiography suite after selective microcatheterization of the feeding vessel and injection of a contrast agent in a dAVF related to the petrous temporal bone. Imaging studies showed the lesion was related to the inferior aspect of the tentorium, warranting a suboccipital surgical approach to treat the fistula.

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)0.001
metaresearch head score (Gemma)0.006
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Case report · Consensus signal: Case report
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.004
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.006
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0040.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0040.002
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 head0.010
GPT teacher head0.256
Teacher spread0.246 · 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 designCase report
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

Citations10
Published2009
Admission routes1
Has abstractyes

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