Prolonged video-EEG reading: Integration of interictal and ictal findings
Bibliographic record
Abstract
長時間ビデオ脳波には、頭皮上はもちろんのこと、頭蓋内脳波においてはさらに膨大な情報量が含まれています。この論文では、てんかん外科の対象となる症例の脳波判読に、是非参考にしていただきたいキーポイントを紹介します。発作間欠期における；1）皮質形成異常にみられる心電図のようにリズミックな棘波、2）Generalized paroxysmal fast activity（GPFA）の側方性、3）REM睡眠時の発作間欠期脳波、発作時に関連した；4）側頭葉てんかんの心電図変化は側方性のヒント、5）筋電図も側方性の重要なヒント、6）皮質形成異常の発作直前に起きている頭蓋内脳波変化（棘波内高周波と除波のパワーバランスの崩壊）、の6つです。これらのポイントを抑えることで、てんかん病態の把握、特に外科適応評価がより確実になると考えています。
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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 | 0.001 |
| 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".