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Record W7010750298

A kutyák circovírusa és kórtani jelentősége = The canine circovirus and its clinical relevance

2023· article· hu· W7010750298 on OpenAlexaboutno aff

Bibliographic record

VenueRepository of the Academy's Library (Library of the Hungarian Academy of Sciences) · 2023
Typearticle
Languagehu
FieldAgricultural and Biological Sciences
TopicAnimal Virus Infections Studies
Canadian institutionsnot available
Fundersnot available
KeywordsPorcine circovirusCircovirusPorcine parvovirusClinical significanceVirusWasting Syndrome
DOInot available

Abstract

fetched live from OpenAlex

A szerzők szakirodalmi adatok alapján összefoglalják a kutyák circovírusával kapcsolatos legfontosabb ismereteket. A kutyacircovírust először 2012-ben azonosították az Amerikai Egyesült Államokban. Ezt követően a vírus jelenléte világszerte leírásra került, mind egészséges, mind klinikai tüneteket mutató egyedekből. Amennyiben a fertőződés klinikai tüneteket okoz, úgy a leggyakrabban gyomor-bélrendszeri tünetek, hasmenés, hányás alakul ki. Ennek ellenére kórtani szerepe a mai napig nem tisztázott teljesen, és gyakran egyéb gyomor-bélrendszeri fertőzést okozó vírussal, főleg kutya-protoparvovírussal (canine parvovirus 2, CPV2) együttesen kerül kimutatásra. Ez utóbbi befolyásolhatja a parvovírus által okozott megbetegedés kórlefolyását, súlyosságát. A kutyacircovírust kedvtelésből tartott kutyák mellett vadon élő állatokból is kimutatták, leggyakrabban vörös rókából (Vulpes vulpes), szürke farkasból (Canis lupus), Norvégiához tartozó Svalbard szigetén élő sarki rókákból (Vulpes lagopus), valamint európai borzból (Meles meles). | The authors in this literature review summarize the most important knowledge \nabout canine circovirus. Circoviruses are small, non-enveloped, highly resistant, \ncircular single-stranded DNA viruses belonging to the family Circoviridae. Circoviruses have been widely detected in pigs, dogs and other carnivores, as well as \nin various avian and fish species. Among the widely studied porcine circoviruses \nare porcine circovirus 1 (PCV1), PCV2, PCV3, and the recently described PCV4. PCV2 \nwas first identified in Canada in the early 1990s. It was first reported in Hungary \nin 1999. Diseases caused by PCV2 include PCV2 systemic disease (formerely \nknown as postweaning multisystemic wasting syndrome), PCV2 reproductive \ndisease, porcine dermatitis and nephropathy syndrome and also subclinical \ninfection. The canine circovirus was first identified in the United States in 2012. \nLater the presence of the virus was described worldwide, both in healthy dogs \nand dogs showing clinical symptoms. The review also gives insights into the \nclinical signs caused by canine circovirus. If the infection is detected in clinically \nill animals, the clinical signs mostly include gastrointestinal symptoms, such as \ndiarrhea and vomiting. Its pathological role, however, has yet to be fully clarified \nto date, and it is often detected together with other gastrointestinal viruses, \nespecially canine protoparvovirus (canine parvovirus 2, CPV2), and furthermore \ncanine herpesvirus, canine distemper virus, canine coronavirus and more rarely \nwith viruses that cause respiratory diseases such as canine parainfluenza virus, \ncanine adenovirus. Canine circovirus infection may influence the prognosis and \nseverity of parvovirus disease. Not least, the present review includes essential \ninformation about canine circovirus infection in wild carnivores based on the \nlatest literature data. Canine circovirus has also been detected in wild animals, \nmostly in red foxes (Vuples vulpes), gray wolves (Canis lupus), arctic foxes (Vulpes lagopus) living on the Norwegian island of Svalbard, and European badgers \n(Meles meles).

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)0.001
metaresearch head score (Gemma)0.003
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: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.007
Threshold uncertainty score0.025

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.001
Science and technology studies0.0010.002
Scholarly communication0.0040.002
Open science0.0000.001
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0070.002

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 head0.062
GPT teacher head0.290
Teacher spread0.228 · 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
Published2023
Admission routes1
Has abstractyes

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