Bibliographic record
Abstract
Long-Term Seizure Outcome after Corpus Callosotomy: A Retrospective Analysis of 95 Patients. Tanriverdi T, Olivier A, Poulin N, Andermann F, Dubeau F. J Neurosurg 2009;110(2):332–342. OBJECT: The authors report long-term follow-up seizure outcome in patients who underwent corpus callosotomy during the period 1981–2001 at the Montreal Neurological Institute. METHODS: The records of 95 patients with a minimum follow-up of 5 years (mean 17.2 years) were retrospectively evaluated with respect to seizure, medication outcomes, and prognostic factors on seizure outcome. RESULTS: All patients had more than one type of seizure, most frequently drop attacks and generalized tonic-clonic seizures. The most disabling seizure type was drop attacks, followed by generalized tonic–clonic seizures. Improvement was noted in several seizure types and was most likely for generalized tonic–clonic seizures (77.3%) and drop attacks (77.2%). Simple partial, generalized tonic, and myoclonic seizures also benefited from anterior callosotomy. The extent of the callosal section was correlated with favorable seizure outcome. The complications were mild and transient and no death was seen. CONCLUSIONS: This study confirms that anterior callosotomy is an effective treatment in intractable generalized seizures that are not amenable to focal resection. When considering this procedure, the treating physician must thoroughly assess the expected benefits, limitations, likelihood of residual seizures, and the risks, and explain them to the patient, his or her family, and other caregivers.
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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".