AED Treatment through Different Ages: As Our Brains Change, Should Our Drug Choices Also?
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Patient age can impact selection of the optimal antiepileptic drug for a number of reasons. Changes in brain physiology from neonate to elderly, as well as changes in underlying etiologies of epilepsy, could potentially affect the ability of different drugs to control seizures. Unfortunately, much of this is speculative, as good studies demonstrating differences in efficacy across age ranges do not exist. Beyond the issue of efficacy, certain drugs may be more or less appropriate at different ages because of differing pharmacokinetics, including changes in hepatic metabolism, absorption, and elimination. Lack of appropriate drug formulations (such as liquid forms) may be a barrier to using drugs in the very young. Finally, some serious adverse events are seen either exclusively or preferentially at different ages.
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.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.005 |
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 it