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Record W4293796498 · doi:10.30954/2277-940x.03.2022.6

Effect of Dietary Protein, Fibre and Lipotropic Factor on the Management of Canine Obesity

2022· article· en· W4293796498 on OpenAlexaboutno aff
Karu Pasupathi, R. Karunakaran, Cecilia Joseph

Bibliographic record

VenueJournal of animal research · 2022
Typearticle
Languageen
FieldMedicine
TopicDiet and metabolism studies
Canadian institutionsnot available
Fundersnot available
KeywordsObesityMedicineDietary managementManagement of obesityVeterinary medicineInternal medicineWeight loss

Abstract

fetched live from OpenAlex

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.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.788
Threshold uncertainty score0.217

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.069
GPT teacher head0.381
Teacher spread0.313 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2022
Admission routes1
Has abstractyes

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