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Record W4404644755 · doi:10.56093/ijvm.v44i2.157676

Ascites in a Labrador retriever puppy with Babesiosis – A case report

2024· article· en· W4404644755 on OpenAlexaboutno aff
P.Udhayabanu, Mayur M. Jadav, Krishantini Mahendran

Bibliographic record

VenueIndian Journal of Veterinary Medicine · 2024
Typearticle
Languageen
FieldImmunology and Microbiology
TopicVector-borne infectious diseases
Canadian institutionsnot available
Fundersnot available
KeywordsPuppyLabrador RetrieverBabesiosisAscitesMedicinePathologyBiologySurgery

Abstract

fetched live from OpenAlex

A 2-month-old male Labrador puppy was presented to Referral Veterinary Polyclinic-Teaching Veterinary Clinical Complex, ICAR- Indian Veterinary Research Institute with a history of inappetence and bilaterally distended abdomen for a period of 15 days. On physical examination, generalized weakness, pale mucous membrane, pyrexia, tachycardia, tachypnea and fluid thrill on the abdomen were noticed. Severe anemia, reduced hematocrit, neutrophilic leukocytosis, hypoproteinemia, hypoalbuminemia and elevated liver enzymes were noticed in haemato-biochemical examination. Babesia sp.was detected in blood smear examination. Ultrasound examination revealed hepatomegaly and ascites. Based on these findings, the case was diagnosed as ascites due to Babesiosis. Forty ml of whole blood was transfused and the animal was treated with Inj. Dextrose, Inj. Imidocarb, Inj. Furosemide for 2 days. Case was discharged with the advice of continuing the treatment with triple drug therapy (doxycycline, clindamycin and metronidazole) for 10 days, hepato-protectant (Susp. Silybon®), haematinic (Syp. Hemobest®) and diuretics (Spironolactone and furosemide combination) orally for 30 days at home and regular follow up. The animal showed uneventful recovery following treatment.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Case report · Consensus signal: Case report
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.036
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.019
GPT teacher head0.286
Teacher spread0.267 · 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 designCase report
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
Published2024
Admission routes1
Has abstractyes

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