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Record W7056982054

Histiocytic sarcoma as a breed specific disease in the Flat-coated retriever

2011· dissertation· en· W7056982054 on OpenAlexaboutno aff

Bibliographic record

VenueHungarian Veterinary Archive · 2011
Typedissertation
Languageen
FieldEngineering
TopicParticle accelerators and beam dynamics
Canadian institutionsnot available
Fundersnot available
KeywordsBreedHistiocytic sarcomaHistiocyteSarcomaLabrador RetrieverMalignant histiocytosis
DOInot available

Abstract

fetched live from OpenAlex

The Flat-coated retriever is a small breed of dogs as far as numbers are concerned, and developed in England in the mid 1800s when the need for a retrieving breed became evident. It is believed to be a mix of several other breeds, with the St. Johns dog from Newfoundland as an important participator. After being very popular at the turn of the century, its popularity declined in the 1920s, and this combined with very little breeding during World War II resulted in a very small number of flats after the war. In 1947 only 75 dogs were registered in England. To save the breed all dogs available were used in breeding, no matter age or faults. Nowadays there are populations of FCRs spread throughout Europe and USA, but it remains a relatively small breed. A problem with tumour diseases (cancer) is recognized in the breed “everywhere”, and researchers have taken an interest in this in several countries. The theory is that this is a genetic disease, and the hunt for the gene(s) responsible has been ongoing for a number of years already. There is especially one type of soft tissue sarcoma that has been dominating among the malignant tumours in this breed, and over the years it has been given several names: undifferentiated soft tissue sarcoma, malignant fibrous histiocytoma, malignant histiocytosis, and histiocytic sarcoma, to mention a few. In recent years the scientists seem to have landed on the term histiocytic sarcoma (HS) as a common name for all these tumours. England, and the University of Cambridge, is the place where the research has been going on the longest, and this is also the place that seems to have achieved most results with their research. However, research is also ongoing in Sweden and the US to find the genes responsible and from there try and find out how to best handle the disease. In Sweden the research is more aimed at cancer in general than HS in particular. For the future we can hope hope that the research will succeed, and that genetic testing of dogs can help in the eradication of the disease, as well as in the therapy of it.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.820
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

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 science0.0010.000
Research integrity0.0000.001
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 head0.026
GPT teacher head0.239
Teacher spread0.213 · 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.

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
Published2011
Admission routes1
Has abstractyes

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