Decreased Subcortical T2 FLAIR Signal Associated with Seizures
Bibliographic record
Abstract
Abnormally decreased T2/T2 FLAIR signal can be seen on brain imaging of patients who are experiencing clinical or subclinical seizures and can be associated with various intracranial pathologies. We identified 29 such patients. The abnormal signal was unilateral in 75.9% of patients. It affected various lobes of the brain, but only in the anterior circulation. In 28 patients (96.6%), there was corresponding decreased signal on DWI. The ADC was normal in all cases. In 26 patients (89.7%), there was corresponding low signal on SWI/gradient recalled-echo; 44.8% of patients underwent contrast-enhanced scans, and there was no abnormal enhancement. Twenty-two (75.9%) patients had documented clinical seizures on the day of imaging. The most frequent concomitant pathology was a subdural hematoma. Electroencephalograms obtained within 24 hours of imaging were available in 65.5%. Findings of all of these electroencephalograms were abnormal, and these electroencephalogram changes were either localized to the area of the abnormal MR imaging signal (where the signal was unilateral) or were bilateral (where the MR imaging changes were bilateral). In summary, decreased white matter T2/T2 FLAIR signal changes can be seen in patients with remarkably similar clinical findings (particularly seizures). These changes are often correlated with abnormal electroencephalogram activity localized to the involved lobes.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".