Bilateral limbic diffusion abnormalities in unilateral temporal lobe epilepsy
Bibliographic record
Abstract
Diffusion tensor magnetic resonance imaging can acquire quantitative information on the microstructural integrity of white matter structures and depict brain connectivity in vivo based on the behavior of water diffusion. Diffusion tensor imaging-derived tractography has been used for virtual dissection of the fornix and cingulum in healthy subjects, but not in patients with temporal lobe epilepsy (TLE). Eight patients with medically intractable TLE and unilateral mesial temporal sclerosis and nine healthy control subjects were imaged using diffusion tensor imaging. Fiber tracking was performed to delineate the fornix and cingulum, which were quantitatively analyzed. Bilateral symmetrical reduction in fractional anisotropy was observed in the fornix of patients with TLE, together with an increase in water mobility perpendicular to the axis of the fibers. The findings in the cingulum are similar to those of the fornix with the exception of significantly increased bulk diffusivity in the latter. We observed strikingly symmetrical bilateral abnormalities of axonal integrity in the fornix and cingulum in a series of patients with unilateral mesial temporal sclerosis. Our findings suggest that TLE with unilateral mesial temporal sclerosis is associated with bilateral limbic system pathology.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| 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".