Investigators' Workshop Sunday Morning Session I�8:00 a.m.-9:30 a.m.
Bibliographic record
Abstract
Jean Gotman*, Hal Blumenfeld†, Amir Shmuel* and Theodore Schwartz‡*Montreal Neurological Institute, Montreal, QC, Canada; †Yale University School of Medicine, New Haven, CT and ‡Weill Cornell Medical College, New York, NY Summary: Epileptic seizures are events during which intense neuronal activity takes place. This neuronal activity is accompanied by important changes in metabolism and blood flow, thought to be the necessary consequence of the energy demands made by neurons. Combined measurements of neuronal activity and metabolism inform us on the coupling between the two phenomena, whether it is normal or pathological and the role it may play in seizure genesis, maintenance or arrest. Neuronal activity may be measured from individual cells or at the cell aggregate level with EEG. Metabolism and blood flow may also be measured locally or at a more global level with fMRI, which has the unique advantage or evaluating simultaneously the whole brain. The workshop will review the fundamental mechanisms of neurovascular coupling in the normal brain, then evaluate expected and unexpected metabolic changes in experimental animal models of epilepsy, and finally see what can be learned from human measurements made before and during epileptic seizures. We will in particular try to interpret what could be the mechanisms of metabolism or blood flow changes that appear to occur a few seconds earlier than neuronal epileptic discharges.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.005 | 0.004 |
| Insufficient payload (model declined to judge) | 0.282 | 0.164 |
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".