Classic or classical ketogenic diet? Definitions and nomenclature
Bibliographic record
Abstract
Dr. Ruby M. Schwartz coined the term "classical" ketogenic diet (KD) in 1989, followed by Dr. Stephen L. Kinsman in the USA, who introduced the term "classic" KD in 1992. Over the next decade, the term "classic KD" became increasingly common. So, which term is preferable-classic or classical? Given the widespread usage, we advocate for consistently using "classic KD." As there is also significant ambiguity about what exactly defines the classic KD compared to other diets, we believe two key aspects are required for the definition of classic KD: the principle of administration and the minimum ketogenic ratio (grams of fat to carbohydrates and protein). Classic KD studies emphasize a tailored, individualized approach to caloric intake and macronutrient distribution, with food items precisely measured. This personalized prescription is the defining feature of classic KD. Recent studies have proposed lower ratios, such as 2:1 or 2.5:1, yet the modified Atkins diet, introduced 80 years later, shows that a 1:1 ratio or lower can also induce ketosis. Therefore, labeling a classic KD with a minimum ratio of 3:1 or 4:1 is misleading. We contend that the classic KD should primarily be defined by its precise, individualized ratios, rather than by an arbitrary minimum value.
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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 | 0.006 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.008 | 0.007 |
| Science and technology studies | 0.002 | 0.011 |
| Scholarly communication | 0.004 | 0.005 |
| Open science | 0.004 | 0.002 |
| Research integrity | 0.003 | 0.007 |
| Insufficient payload (model declined to judge) | 0.003 | 0.002 |
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".