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Record W3181012254 · doi:10.21887/ijvsbt.17.2.3

Studies on Clinico-Etio-Epidemiology of Vomition in Dogs

2007· article· en· W3181012254 on OpenAlexaboutno aff
Rimjhim . Khanduri, Sunant K. Raval, Dasharath B. Sadhu, B. B. Bhanderi, Divdyesh N. Kelawala, Keshank Dave

Bibliographic record

Venue˜The œIndian journal of veterinary sciences and biotechnology · 2007
Typearticle
Languageen
FieldMedicine
TopicHerpesvirus Infections and Treatments
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineIncidence (geometry)AnorexiaVomitingEpidemiologyAbdominal painDiarrheaEtiologyBreedVeterinary medicineBeagleInternal medicineGastroenterologyBiology

Abstract

fetched live from OpenAlex

The present study of etio-epidemiology of vomition in dogs was carried out amongst the dogs presented at Veterinary Clinical Complex, AAU, Anand. A total of 50 cases of vomiting dogs were selected for this study. Investigation of etiological factors associated with vomition revealed that 50.00% vomiting cases were due to dietary abnormalities, 24.00% due to Parvo viral infection, 10.00% due to parasitic infestation, 8.00% renal disorders, 6.00% due to hepatic disorders, and 2.00% due to pyometra. The epidemiological parameters like sex, breed, and age were recorded. During the sex-wise incidence of vomition was found more in male (64.00 %) than in female (36.00 %) dogs. The breed-wise incidence of vomition was recorded highest (32.00 %)in Mongrel, followed by Labrador Retriever (28.00 %), Spitz (12.00 %), Doberman Pinscher (8.00 %), German Shepherd (10.00 %), Great Dane 4%, Beagle (2.00 %), Lasa Aphso (2.00 %), and Pug (2.00 %) . The age-wise incidence of vomition was recorded higher (58.00%) in 0-6 months age group, followed by (24%) in 7 months to 3 years age group and (18%) in 3-8 years age group. Clinical examination revealed dehydration, dullness, congested to anemic mucus membranes, inappetence to anorexia, tachycardia, melaena, haematemesis, diarrhea, and clear lungs. On abdominal palpation, there was mild pain in dogs affected with renal and hepatic disorders.

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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.480
Threshold uncertainty score0.401

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 studies0.0000.001
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 head0.118
GPT teacher head0.416
Teacher spread0.299 · 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
Published2007
Admission routes1
Has abstractyes

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