Bibliographic record
Abstract
PURPOSE: A patient with a distinct aura of prescience as a manifestation of temporal lobe epilepsy was encountered. The experience prompted a review of this ictal phenomenon among patients attending a tertiary care epilepsy outpatient clinic. METHODS: A computer epilepsy database was searched for patients with simple partial sensory seizures and complex partial seizures with auras. Identified patients had charts reviewed for details of the auras; patients were contacted and asked to provide written descriptions of their experiences. Literature searches (PubMed) were done by using the terms "precognition" or "prescience" and "seizures" or "epilepsy." Standard comprehensive epilepsy textbooks were reviewed. RESULTS: The charts of 218 patients were reviewed from 927 in the database; three had prescience as an ictal feature. The patients' descriptions were very similar in all cases (a profound sense of "knowing" what was going to happen in their environment in the immediate future). The experience was distinct from déjà vu and other psychic experiences. All patients probably have temporal lobe epilepsy. Only one other description of prescience as an ictal feature was found in the literature. CONCLUSIONS: Prescience can occur as an ictal feature of temporal lobe epilepsy and represents a previously underreported psychic phenomenon. The potential lateralizing value of this symptom is yet to be determined.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".