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Record W7066658093

Inherited and breed standard related defects in purebred dogs; the Boxer, English bulldog, Great Dane and Newfoundland dog

2014· dissertation· en· W7066658093 on OpenAlexaboutno aff

Bibliographic record

VenueUtrecht University Repository (Utrecht University) · 2014
Typedissertation
Languageen
FieldEconomics, Econometrics and Finance
TopicDiverse Scientific and Economic Studies
Canadian institutionsnot available
Fundersnot available
KeywordsPurebredPopulationDiseaseBreedChristian ministryEpidemiology
DOInot available

Abstract

fetched live from OpenAlex

In the Netherlands, there are approximately 300 different dog breeds and purebred dogs are becoming more popular. The physical appearance, which is recorded in the breed standard, can however be connected with some negative features. Purebred dogs can be more susceptible for diseases. These diseases can be directly related to the physical appearance, or it can be a genetic condition which is found in the breed. It is impossible to create a disease free dog breed, but it should be a priority to try to eliminate the diseases found in the breed which are deleterious for the dog’s welfare. The goal of this study is to investigate the diseases found in four popular dog breeds in the Netherlands: the Boxer, English Bulldog, Great Dane and Newfoundland dog. The research is commissioned by the LICG (Landelijk Informatie Centrum Gezelschapsdieren) and the Ministry of Economic affairs.\nThe analysis consists of two parts, a scientific literature study and study of the University Clinic for Companion Animals (UKG) database.\nEach of the studied breeds have many predisposed diseases described in scientific literature, both related and non-related to the conformation.\nThe UKG analysis revealed which organ systems were most often associated with disease compared to crossbreeds. It also indicated which diseases were diagnosed in those organ systems. The analysis revealed overrepresented disciplines for every breed, except the Great Dane.\nImportant diseases of Boxers in the Netherlands are subvalvular aortic stenosis, chronic kidney disease (CKD), cystitis, anterior cruciate ligament rupture, seasonal follicular dysplasia, lymphoma and mastocytoma.\nThe most important disorders for the English Bulldog population in the Netherlands are Brachycephalic airway obstruction syndrome (BAOS), entropion, prolapse of the nictitans gland, dystocia and pododermatitis.\nImportant diseases for the Great Dane population in the Netherlands are: deafness (congenital), gastric torsion, dilated cardiomyopathy (DCM), and osteosarcoma.\nThe most important diseases for the Newfoundland dog are subvalvular aortic stenosis, dilated cardiomyopathy (DCM) and hip dysplasia.\nThe results of the analysis will form the qualitative basis for the purebred dog guide of the LICG, which will be combined with quantitative data of the Dutch dog population gathered from primary veterinary practices in a later stadium. The information can help breeders form a health policy for the breed and it can inform consumers on choosing a breed when buying a purebred dog.

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)0.001
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.028
Threshold uncertainty score0.056

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.001
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.009
GPT teacher head0.160
Teacher spread0.151 · 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
Published2014
Admission routes1
Has abstractyes

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