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Record W7110974743 · doi:10.32718/nvlvet-a10309

Analysis of feeding of German Shepherd dogs using BARF for the prevention of constipation (in the conditions of the Canine Training Center of the State Border Guard Service of Ukraine in the city of Velyki Mosty, Lviv region)

2025· article· uk· W7110974743 on OpenAlexaboutno aff

Bibliographic record

VenueScientific Messenger of LNU of Veterinary Medicine and Biotechnologies · 2025
Typearticle
Languageuk
FieldEnvironmental Science
TopicScientific Research and Studies
Canadian institutionsnot available
Fundersnot available
KeywordsGerman Shepherd DogGuard (computer science)WithersAnimal healthBody weightService (business)GermanAnimal welfare

Abstract

fetched live from OpenAlex

The materials of the publication analyze the effect of feeding German Shepherd dogs using BARF for the prevention of constipation, as well as the health and performance of experimental service dogs in the conditions of the Canine Training Center of the State Border Guard Service of Ukraine, located in the city of Velyki Mosty, Lviv region. The feeding ration of service dogs adopted at the KNC of the State Border Guard Service of Ukraine generally meets the needs of young German Shepherds and provides a sufficient level of energy, proteins, vitamins and minerals for normal growth, development and service loads of dogs. Their live weight increased by 4.1 kg, height at the withers by 3.2 cm. The animals of the experimental group that received the experimental diet increased their live weight by 5.1 kg and their height at the withers by 4.2 cm, which indicates that the proposed feeding of dogs using BARF is a better diet for the health of animals and their productive qualities than that accepted at the Canine Training Center of the State Border Guard Service of Ukraine. BARF (Bones And Raw Food diet or Biologically Appropriate Raw Food diet) is a dog nutrition system based on raw natural products. That is, BARF stands for “biologically appropriate raw food”. That is, it is natural food for dogs and cats that corresponds to their natural way of consumption. BARF diets are based on the recommendations of FEDIAF (European Pet Food) – the European Guide to Animal Nutrition and Responsible Animal Care – the main book of feed ration recipes. All leading companies produce BARF food lines and offer them to pet owners. BARF also does not involve heat treatment of products – all rations consist exclusively of raw, fresh and frozen products. In particular, food does not require further heat treatment – to feed the animal, it is enough to defrost the food package. Heat-treated products lose useful and nutritious elements; At the same time, the body of carnivorous animals (dogs and cats) is not designed to digest heat-treated products, so the level of digestibility of boiled, baked, etc. dishes will be significantly lower. BARF or raw feeding is becoming increasingly popular among dog lovers in Canada and Germany. BARF is a complete product containing raw meat, fresh vegetables, fruits and additives such as oils and herbs.

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 imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.002
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
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)0.0010.000

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 head0.145
GPT teacher head0.404
Teacher spread0.259 · 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 source (direct Gemma or distilled Codex), 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
Published2025
Admission routes1
Has abstractyes

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