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Record W3199746330 · doi:10.30466/vrf.2020.116932.2778

Phylogenetic analysis and pathological characterization of fowl adenovirus isolated during inclusion body hepatitis outbreak in Tubas, Palestine.

2021· article· en· W3199746330 on OpenAlexaboutno aff
Ibrahim Alzuheir, Nasr Jalboush, Adnan Fayyad, Rosemary Daibes

Bibliographic record

VenuePubMed · 2021
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicVirus-based gene therapy research
Canadian institutionsnot available
Fundersnot available
KeywordsGenBankSerotypeBiologyVirologyPhylogenetic treeOutbreakFowlBroilerGeneGenetics

Abstract

fetched live from OpenAlex

Fowl adenoviruses (FAdVs) associated with inclusion body hepatitis (IBH) was identified in commercial broiler chickens in Palestine. Investigated birds showed primary clinical signs and lesions of IBH including growth retardation, congested and enlarged liver with necrosis, petechial hemorrhage and basophilic intra-nuclear inclusion bodies. The mortality rate was from 15.00%. The FAdV was detected and sequenced in the liver samples of infected chicken by polymerase chain reaction using hexon gene-specific primers. Phylogenetic analysis revealed that FAdVs belong to FAdV-D serotype 10, clustered within the European highly pathogenic isolates. The highest nucleotide sequence similarity was 99.48% with highly pathogenic FAdV-D serotype 10 detected from infected chicken in Poland (GenBank: LN907532.1) and FAdV-D from infected chicken in Sweden (GenBank: HE961828.1). The lowest similarity was 93.46% with Canadian FAdV-D (GenBank: EF685576.1). In conclusion, this is the first report describing the presence of IBH revealing that the causative virus is closely similar to the highly pathogenic FAdV-D serotype 10 of IBH in broiler chickens in Palestine.

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 score0.009
Threshold uncertainty score0.018

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)0.0000.000

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 head0.011
GPT teacher head0.240
Teacher spread0.229 · 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

Citations6
Published2021
Admission routes1
Has abstractyes

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