Effect of Dietary Protein, Fibre and Lipotropic Factor on the Management of Canine Obesity
Bibliographic record
Abstract
The study formulated and evaluated different therapeutic diets viz., high protein high fibre (T 2 ), high protein medium fibre (T 3 ) and choline supplemented diet (T 4 ) for the management of canine obesity against the control (normal adult dog maintenance diet, T 1 ) in 24 Labrador retriever obese dogs selected on the basis of their body condition score (BCS) and body weight and randomly distributed into 4 groups and fed therapeutic diets for a period of four months.The change in BCS, body weight, dry matter intake and caloric intake were recorded at fortnightly intervals.Dogs on T 2 diet (21.90 % CP and 11.28 % CF diet) recorded loss 30.3 g/d while on T 3 diet (21.73 % CP and 8.23 % CF diet) lost 17.67 g/d.Body condition score was reduced 5.04 and 3.03 per cent in T 2 and T 3 , respectively.Thus, the result indicated increase of 21% protein and 11% fiber in diet helped to improve weight loss 5 to 8% in dogs in 4 months period. HIGHLIGHTSm Formulation of diet for canine obesity.m Supplementation of 21% protein and 11% fiber in diet helped to improve weight loss 5 to 8% in dogs in 4 months period.
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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 | 0.000 |
| 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 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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".