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Record W2001320357 · doi:10.1212/wnl.0b013e3181cc0b60

Teaching Neuro <i>Images</i> : Middle cerebral artery aneurysm rupture presenting as pure acute subdural hematoma

2010· article· en· W2001320357 on OpenAlexaff
Thalia S. Field, Manraj K.S. Heran

Bibliographic record

VenueNeurology · 2010
Typearticle
Languageen
FieldMedicine
TopicCerebral Venous Sinus Thrombosis
Canadian institutionsVancouver General Hospital
Fundersnot available
KeywordsMedicineAneurysmSubarachnoid hemorrhageSubarachnoid spaceHematomaMiddle cerebral arteryIntracranial pressureSubdural hemorrhageSurgeryBlurred visionCardiologyPathologyIschemiaCerebrospinal fluid

Abstract

fetched live from OpenAlex

A previously well 33-year-old man with no history of trauma or substance abuse presented with poor right eye visual acuity, somnolence, and vomiting several hours after sudden onset of severe, persistent headache.Examination revealed only a right relative afferent papillary defect and subretinal blood on funduscopy (Terson syndrome, figure 1A).Hunt and Hess grade was 3.CT showed right subdural and subhyaloid hemorrhages (figure 1, B and C).Angiography re-vealed a right middle cerebral artery aneurysm (figure 2).Aneurysm rupture rarely presents as pure acute subdural hematoma.Proposed mechanisms involve direct aneurysm rupture into subdural space, from orientation, adherence to dura, or rupture through subarachnoid space by a superficial or high-pressure bleed. 1 Terson syndrome refers to intraocular hemorrhage with aneurysm rupture.Proposed pathophysiology includes retinal venous bleeding from stasis secondary to increased intracranial pressure, or from blood forced into the subarachnoid space and then along the optic nerve sheath into the preretinal space under pressure.2 Coronal (A) and sagittal (B) views demonstrating bilobed aneurysm at the middle cerebral artery trifurcation.There was no evidence of an arteriovenous dural 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)0.000
metaresearch head score (Gemma)0.002
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 score0.014
Threshold uncertainty score0.047

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.001
Science and technology studies0.0020.001
Scholarly communication0.0010.002
Open science0.0010.001
Research integrity0.0030.003
Insufficient payload (model declined to judge)0.0140.003

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 head0.012
GPT teacher head0.254
Teacher spread0.242 · 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

Citations6
Published2010
Admission routes1
Has abstractyes

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