Bibliographic record
Abstract
By the year 2005 the senior author had carried out over 2500 surgical procedures for the treatment of intractable epilepsies. The procedures were all carried out at the Montreal Neurological Institute and Hospital. Most of the surgical approaches and techniques of brain mapping and cortical resections were taught to me by Theodore Rasmussen. I was fortunate enough to practice neurosurgery during a period which saw dramatic improvement in neurosurgical techniques, namely microsurgery and image-guided surgery. Most of the microsurgical techniques had been applied to extracerebral vascular and tumoral lesions. We made a constant effort to apply these techniques to the intragyral endopial resection. In 1992, we started applying neuronavigation to virtually all procedures for epilepsy from preoperative brain mapping to intracranial recording and various types of cortical resections. The book is mainly concerned with surgical techniques in epilepsy and reflects the authors’ bias concerning the importance of mastering the trilogy of topographic, vascular and functional anatomy of the brain. It is not only a book on surgical techniques but also a guide for neurosurgeons who specialize or will specialize in that field. I like to think of it as a manual for the Fellows in Epilepsy Surgery, to help them understand in a practical way the basic anatomical and physiological mechanisms of epilepsy and the clinical seizure patterns leading to the surgical hypothesis. The best surgical techniques will only be effective if applied to well-selected patients with sound indications. The neurosurgeon must be familiar with all the investigation techniques and especially those of intracranial recording and stimulation. He must develop consultant skills; skills in evaluating the patient, not only as a surgical candidate but as an individual overwhelmed by the occurrence of seizures who could have false expectations of surgery. He must develop skills in teaching basic anatomy to patients and their families for their own understanding. The neurosurgeon must develop also a technique for database collection for each patient where the essential of his history and investigation are gathered and fully analyzed before any decision to operate is reached. This will go a long way to avoid pitfalls which can result not only from lack of knowledge of surgical anatomy and poor surgical techniques but also from inadequate patient selection.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.298 | 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".