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Record W2063383658 · doi:10.1177/0883073811420293

Fetal Opercular Cavernous Angioma Causing Cerebral Cleft

2011· article· en· W2063383658 on OpenAlexafffund
Harvey B. Sarnat, Xing‐Chang Wei, Laura Flores‐Sarnat, Cynthia Trevenen, Karen Barlow

Bibliographic record

VenueJournal of Child Neurology · 2011
Typearticle
Languageen
FieldMedicine
TopicVascular Malformations Diagnosis and Treatment
Canadian institutionsAlberta Children's HospitalUniversity of Calgary
FundersCalgary Laboratory ServicesUniversity of Calgary
KeywordsPorencephalyAngiomaFetusMedicineNeuroimagingGerminal matrixMagnetic resonance imagingPolymicrogyriaAnatomyDysgenesisCerebrumPathologyRadiologyPregnancyVascular diseaseCentral nervous systemGestational ageIntraventricular hemorrhageSurgeryInternal medicineBiology

Abstract

fetched live from OpenAlex

We describe a 22-week female fetus after pregnancy was terminated because of fetal magnetic resonance imaging showing a large left cerebral hemispheric cleft suggestive of porencephaly or schizencephaly. Postmortem examination revealed a large cavernous angioma of the left opercular region with evidence of previous hemorrhage and extensive cerebral infarction. In the right hemisphere, another vascular malformation within the frontal germinal matrix consisted of an aggregate of primitive vessels not yet canalized. Selective dysgenesis of the right subiculum also was demonstrated. This case illustrates not only a severe encephaloclastic effect of cavernous angioma in fetal brain but also the importance of fetal autopsy to help correlate and explain fetal neuroimaging. Potential future prenatal treatment of fetal angiomata requires precise in utero diagnosis.

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 score0.002
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0010.001
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.021
GPT teacher head0.237
Teacher spread0.216 · 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

Citations1
Published2011
Admission routes2
Has abstractyes

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