Bibliographic record
Abstract
The Ketogenic Diet (KD) has been used in treatment of epilepsy in mainland China since 2004.Clinical indications of KD include: Glucose Transporter Type 1 (GLUT-1) deficiency, Pyruvate Dehydrogenase Deficiency (PDHD, myoclonus-astatic epilepsy (Doose syndrome), tuberous sclerosis complicated with or without epilepsy, Rett syndrome, Dravet syndrome, infantile spasms, and Landau-Kleffner syndrome, Lafora disease, and super-refractory status epilepticus.The contraindications of KD include: Inborn error of lipid metabolism, porphyria, and patients who are unable to cooperate with the KD.There should be standardized clinical consultation and evaluation before starting KD treatment; and special attention should be paid to selection and preparation of food, and to indication of age and geographic area etc.During the KD treatment, the transition time from ordinary diet to KD often takes 1-2 weeks; and a final 2: 1-4: 1 ketogenic diet ratio will normally produce ketosis of clinical therapeutic effect.The KD could be combined with anticonvulsant treatment.A qualified ketogenic diet therapy means: (1) Proper nutrition and growth with normal nutrition biomarkers; (2) Tasty foods: patients are willing to accept the therapeutic diet; (3) Ideal state of ketosis: urine ketone remains above (+++), blood ketone at about 4.0 mmol/L, blood sugar is controlled at 4.0 mmol/L, ratio of blood sugar/blood ketone is about 1: 1-2: 1; (4) Reasonable balanced food composition, defecate daily and naturally without constipation; (5) No remarkable complication(s).It is recommended that KD could be tried at least for three months continuously.Good responders should maintain the KD therapy for 2 yrs.or so.It often needs to take 3-6 months to return back to a regular diet.KD therapy should be monitored with close follow-ups and assessments.Our extensive experience has confirmed that it is safe in clinical practice.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".