Bibliographic record
Abstract
Objectives: Approximately 20% of epileptic children resist anti-seizure medications (ASMs). Management of these cases is complex and needs many pre-requisites. A Gene study is a part of the assessment in epilepsy cases and adjusts according to the physician’s decision. We conducted a gene study and assessed the response to ASMs. Material & Methods: All the ASMs resistant cases that were suspected of genetic epilepsy, did not have metabolic/structural etiology or neurodegenerative disease, and were referred for genetic study between Jan 2014 to Dec 2021 were enrolled. The records of 52 cases were assigned in our registry. The name of the gene extracted and the response to ASMs evaluated. The mean age was 6.65 years old; 24 (46.2%) were boys and 28 (53.8%) were girls. Results: The most common found genes were SCN1A, CAD1, IQSEC2, SLc6A1, AP3B2, SLC25A22, and KCNJ10. The complete response rate was seen in 20 cases (38.46%). Conclusion: In conclusion, further studies should be profit to make a link between gene type and drug response and achieve a better seizure- free response. If this happened, precision medicine would be more achievable
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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.004 | 0.001 |
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".