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Record W2294067095 · doi:10.1177/1971400916638357

Cerebral aneurysm debuting as rupture during diagnostic CT angiography: An unexpected worst-case scenario

2016· article· en· W2294067095 on OpenAlexaff
Adam A. Dmytriw, Jaime L. Martínez, Julian Spears, Thomas R. Marotta

Bibliographic record

VenueThe Neuroradiology Journal · 2016
Typearticle
Languageen
FieldMedicine
TopicIntracranial Aneurysms: Treatment and Complications
Canadian institutionsSt. Michael's Hospital
Fundersnot available
KeywordsAsymptomaticDigital subtraction angiographyMedicineAneurysmRadiologyAngiographyComputed tomographic angiographyCerebral angiographyComputed tomography angiographySurgery

Abstract

fetched live from OpenAlex

Previously-asymptomatic intracranial aneurysm rupture during cerebral angiography is an extremely rare phenomenon. There is a small risk of rupture of these aneurysms during digital subtraction angiography (DSA), but no case of spontaneous rupture during computed tomographic angiography (CTA) has been reported. A concise case of a 40-year-old woman referred for workup of an asymptomatic intracranial aneurysm who experienced acute rupture at the time of identification of a second aneurysm is described. This case highlights the potential for rupture at the time of scan acquisition and the importance of maintaining a high level of suspicion in the setting of neurological deterioration, as well as the potential need by all medical imaging professionals to identify an emergency and activate an urgent 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)0.001
metaresearch head score (Gemma)0.007
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 score0.005
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.007
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.001
Science and technology studies0.0030.002
Scholarly communication0.0030.002
Open science0.0010.002
Research integrity0.0050.004
Insufficient payload (model declined to judge)0.0020.001

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 head0.015
GPT teacher head0.257
Teacher spread0.243 · 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

Citations3
Published2016
Admission routes1
Has abstractyes

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