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Record W2995760763 · doi:10.1016/j.radcr.2019.10.029

Reversible sulcal FLAIR hyperintensity on MRI in a migraine patient with aura

2019· article· en· W2995760763 on OpenAlexaff
Eduardo Portela de Oliveira, Vered Tsehmaister-Abitbul, Mario Kontolemos, Rafael Glikstein, Carlos Torres

Bibliographic record

VenueRadiology Case Reports · 2019
Typearticle
Languageen
FieldMedicine
TopicMigraine and Headache Studies
Canadian institutionsOttawa HospitalUniversity of Ottawa
Fundersnot available
KeywordsFluid-attenuated inversion recoveryHyperintensityMedicineAuraAbnormalityMigraineHeadachesMagnetic resonance imagingRadiologyMigraine with auraNeuroimagingNeurologyInternal medicineSurgeryPsychiatry

Abstract

fetched live from OpenAlex

Reversible sulcal fluid-attenuated inversion recovery (FLAIR) hyperintensity is a rare imaging finding that could be seen on magnetic resonance imaging (MRI), in patients with migraine with aura. Herein, we present a patient who was admitted to the emergency department with severe headaches, numbness on the right side of the body, and visual changes. MRI showed sulcal FLAIR hyperintensity in the occipital lobes, with no other abnormality. The patient was diagnosed with migraine with aura by neurology and the follow up MRI showed resolution of the finding, supporting the diagnosis. Sulcal hyperintensity on FLAIR is a nonspecific imaging finding that can occur with or without cerebral spinal fluid (CSF) abnormality. Although, clinical correlation and CSF analysis may be required, radiologists may often be able to suggest the cause of abnormal CSF signal depending on the distribution of sulcal FLAIR hyperintensity, and the presence of additional imaging findings.

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 score0.007

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 studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0020.001
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 head0.010
GPT teacher head0.240
Teacher spread0.230 · 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

Citations7
Published2019
Admission routes1
Has abstractyes

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