Bibliographic record
Abstract
More than 28,000 neuroscientists and 3,000 epileptologists gathered at their respective 2001 meetings of the Society for Neuroscience and the American Epilepsy Society. Yet only six articles, one directly and five indirectly, discussed the corpus callosum (CC). Is not this in itself a remarkable finding? Are there no mysteries left? The reality is that considerable uncertainties exist regarding the rationale for callosal bisection (CCB) that causes contrasting effects (i.e., amelioration of generalized seizure, at times leading to freedom from seizure, and intensification of postoperatively fragmented seizure, at times leading to status epilepticus). Similarly, the clinical relevance of EEG mirror focus formation, an experimentally well-established transcallosal consequence of partial cortical epileptogenesis, continues to be debated. This presentation revisits these unresolved issues (a) to gain insight into the dynamic role played by the CC in medically refractory epilepsy, and (b) to promote the development of antiepileptogenic tools that are currently unavailable.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.002 |
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".