Serum Aspartic Acid as a Marker of Epilepsy
Bibliographic record
Abstract
OBJECTIVE: Determine the diagnostic validity of serum aspartic acid as a predictor of epilepsy. STUDY DESIGN & METHODOLOGY: This study enrolled 80 epileptic patients and 80 healthy people, and we measure serum level of aspartic acid by using high liquid performance chromatography. RESULTS: Mean serum aspartic acid was significantly higher in patients (26.2 ± 10.1) mg\dl while in control was (2.8 ± 1.36) mg\dl, the result showed that aspartic acid is an excellent predictor area under the curve [AUC] (95%CI) = 0.988 (0.97 – 1.0) with 96.3% sensitivity and 97.5% specificity for epileptic patients. Also, the result shows generalized seizure has significantly higher mean serum aspartic acid compared to partial type and GTC show significantly higher mean serum aspartic acid compared to myoclonus. CONCLUSION: Aspartic acid serum level markedly elevated in epileptic patients groups in comparison to the healthy group, also shows a marked difference between generalized and partial epilepsy and show different levels between subtypes of epilepsy.
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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 | 0.001 | 0.003 |
| 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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".