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Diagnosis of subclinical stage of Babesia gibsoni and its’s therapeutic management in dogs

2023· article· W4416304208 on OpenAlexaboutno aff
N Aishwarya, Shaik Ruksana, Andrea K. Ng

Bibliographic record

VenueThe Pharma Innovation · 2023
Typearticle
Language
FieldImmunology and Microbiology
TopicVector-borne infectious diseases
Canadian institutionsnot available
Fundersnot available
KeywordsBeagleSubclinical infectionLabrador RetrieverStage (stratigraphy)Antibiotic therapyDoxycycline

Abstract

fetched live from OpenAlex

A total of 10 dogs of different breeds namely Beagle (1 year), Mudhol (11 months), Belgian Malinois (7 months), Shih Tzu (2 years), Labrador (10 year), Pug (5 years), Golden Retriever (2 months), Siberian Husky (9 months), Shih Tzu (1 year), Dachshund (3 years) were presented to Kamala Pet Care, Nagarbhavi, Bangalore, Karnataka with the complaint of dull, inactive, inappetence some pet with history of vomition and blood motion for two to three days and some other pet showed episodes of seizure. Hematobiochemical parameters were within the normal range. The condition was diagnosed as Babesia gibsoni using treated with Diminazine aceturate (Berenil®) along with triple antibiotic and supportive therapy. all the cases were recovered eventually after the 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 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: Case report · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.001
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 head0.055
GPT teacher head0.343
Teacher spread0.288 · 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 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
Published2023
Admission routes1
Has abstractyes

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