MétaCan
Menu
← Back to cohort
Record W4297781198 · doi:10.5281/zenodo.7069563

Canine Parvovirus in Jalukie, Nagaland

2022· article· en· W4297781198 on OpenAlexaboutno aff
Summyangma Limboo Subba

Bibliographic record

VenueZenodo (CERN European Organization for Nuclear Research) · 2022
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicVirus-based gene therapy research
Canadian institutionsnot available
Fundersnot available
KeywordsCanine parvovirusParvovirusVirologyMedicineVirus

Abstract

fetched live from OpenAlex

Canine Parvovirus [CPV] infection is a global infectious and highly contagious viral disease of canine, resulting in severe GIT disease and occasionally cardiac disease with high morbidity rate (up to 100%) and frequent mortality (up to 10%) (Anum, 1979). The pathogenicity and transmission of this virus is amazingly quick due to its unusual high contagiousness. The virus responsible for Canine Parvovirus is a non-enveloped DNA virus. Canine Parvovirus is a stable virus that can survive for up to 5-7 months in the environment, this means, susceptible dogs can contract the virus simply by coming in contact with the environment that had been contaminated months back. In the Teaching Veterinary clinical complex of CoVSc, Jalukie, Nagaland, it has been observed that dogs between 2-6 months of age which were not vaccinated indicated the highest prevalence. The condition is found to be more severe when the puppies are neither vaccinated nor dewormed. Dogs of any breed, be it non-descriptive (local) dogs or exotic breeds like German Shepherd, Golden Retriever, Doberman, and Labrador etc. are susceptible to this infection. Among different risk factors, young unvaccinated puppies and exotic breeds were more prone to CPV infection. Regarding the season, the highest prevalence was noticed in the month of December to February, i.e. during winter season.

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)0.000
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.064
Threshold uncertainty score0.127

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.024
GPT teacher head0.258
Teacher spread0.234 · 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 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
Published2022
Admission routes1
Has abstractyes

Explore more

Same venueZenodo (CERN European Organization for Nuclear Research)→Same topicVirus-based gene therapy research→French-language works237,207→