Susceptibility to Febrile Seizures: More Than Just a Faulty Thermostat!
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
Febrile seizures, always a hot topic, continue to fire up the interest of a wide spectrum of clinical and basic neuroscientists. Several clinical investigators, amongst them the Halifax group (spearheaded by the Camfields to whom we owe a great debt of gratitude for their contributions in this field), have provided us with a sound foundation for clinical management. We now need to explore febrile seizures in new ways to clarify factors and identify mechanisms that contribute to the intriguing age-dependent susceptibility. The complex processes involved in thermoregulation and the febrile response are important pieces of the puzzle. The contributory factors are likely different for isolated simple febrile, recurrent febrile and complex febrile seizures. A 'systems biology approach' is needed to investigate the intricate genome-proteome-metabolome interaction in determining susceptibility. Population studies that incorporate current clinical, experimental, infectious and molecular genetic knowledge in their concept and design will help to 'conquer' the final frontiers of febrile seizures. In 2006, Engel suggested that febrile seizures could 'encompass many different entities', an increasingly plausible opinion. A higher profile for febrile seizures and related syndromes in the ILAE classification scheme will further catalyze progress in the field. The resultant knowledge can only improve management.
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 | 0.005 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.004 | 0.008 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.003 | 0.000 |
| Research integrity | 0.001 | 0.006 |
| 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 it