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Record W4382992056 · doi:10.59565/dadu1125

Traditional Chinese Veterinary Medicine Approach to Canine Splenic Hemangiosarcoma

2023· article· en· W4382992056 on OpenAlexaboutno aff

Bibliographic record

VenueAmerican Journal of Traditional Chinese Veterinary Medicine · 2023
Typearticle
Languageen
FieldMedicine
TopicVeterinary Oncology Research
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineSplenectomyHemangiosarcomaChemotherapySpleenSurgeryGastroenterologyInternal medicine

Abstract

fetched live from OpenAlex

Hemangiosarcoma (HSA) is a highly malignant tumor of endothelial cells that comprises approximately 50% of all splenic neoplasms in dogs. It commonly afflicts older, large breed dogs, particularly Golden retrievers, Labrador retrievers and German shepherds. Affected dogs often present for evaluation of acute collapse due to tumor rupture and abdominal hemorrhage. Standard treatment of canine splenic HSA includes splenectomy and subsequent chemotherapy. There are several reported chemotherapy protocols, most of which involve the use of intravenous doxorubicin. Survival rates for dogs with splenic HSA are generally poor. Treatment with surgery (splenectomy) only provides a mean survival of 1-3 months with affected dogs generally succumbing to recurrent and/or metastatic disease. Surgery and chemotherapy improve survival times slightly to a median survival time of 4-6 months. Experiential experience by the authors have noted a better clinical outcome can be achieved using traditional Chinese veterinary medicine (TCVM) treatment. Dogs treated with splenectomy and TCVM have survival times of 3-4 years with a good quality of life. The TCVM treatment survival time for the HSA dogs without splenectomy averages 11-13 months. The primary TCVM Patterns of splenic HSA are Qi Deficiency, Blood Deficiency, and Blood Stasis. This paper will review TCVM Pattern diagnosis and treatment of HSA in dogs along with a case series of 4 dogs.

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)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.589
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0030.001
Bibliometrics0.0030.005
Science and technology studies0.0000.003
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
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 head0.137
GPT teacher head0.382
Teacher spread0.245 · 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

Citations1
Published2023
Admission routes1
Has abstractyes

Explore more

Same venueAmerican Journal of Traditional Chinese Veterinary MedicineSame topicVeterinary Oncology ResearchFrench-language works237,207