Bibliographic record
Abstract
The domestic cat's wild ancestors are obligate carnivores that consume prey containing only minimal amounts of carbohydrates. Evolutionary events adapted the cat's metabolism and physiology to this diet strictly composed of animal tissues and led to unique digestive and metabolic peculiarities of carbohydrate metabolism. The domestic cat still closely resembles its wild ancestor. Although the carnivore connection of domestic cats is well recognised, little is known about the precise nutrient profile to which the digestive physiology and metabolism of the cat have adapted throughout evolution. Moreover, studies show that domestic cats balance macronutrient intake by selecting low-carbohydrate foods. The fact that cats evolved consuming low-carbohydrate prey has led to speculations that high-carbohydrate diets could be detrimental for a cat's health. More specifically, it has been suggested that excess carbohydrates could lead to feline obesity and diabetes mellitus. Additionally, the chances for remission of diabetes mellitus are higher in cats that consume a low-carbohydrate diet. This literature review will summarise current carbohydrate knowledge pertaining to digestion, absorption and metabolism of carbohydrates, food selection and macronutrient balancing in healthy, obese and diabetic cats, as well as the role of carbohydrates in prevention and treatment of obesity and diabetes mellitus.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| 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".