A Low Carbohydrate, High Protein Diet May Extend Your Life and Reduce Your Chances of Getting Cancer
Bibliographic record
Abstract
When glucose in our blood enters our cells it is broken down via glycolysis to pyruvate. Pyruvate can then be converted to lactic acid and secreted, ending glycolysis, or into acetyl-CoA and broken down, with the help of oxygen (O 2 ), within mitochondria to carbon dioxide (CO 2 ) and water via oxidative phosphorylation (OXPHOS, i.e., the Kreb’s, Citric acid or tricarboxylic acid cycle) 1 . In 1857 Louis Pasteur discovered that in the absence of O 2 , normal cells survive by switching from OXPHOS, which generates 36 ATPs/glucose, to glycolysis, which only generates 2 ATPs/glucose. In the 1920s, Otto Warburg found that cancer (CA) cells, unlike normal cells, use glycolysis instead of OXPHOS even when O 2 is present, and this is called “aerobic glycolysis” or the ‘Warburg effect’ 1 . Because most tumours use this less efficient energy generating system, they have to take up more blood glucose (BG) than normal cells to survive and this is the basis for identifying human CAs using PET scans with the glucose analog, 18 fluorodeoxyglucose 2
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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 | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.040 | 0.008 |
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".