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Record W2747867354 · doi:10.3390/v9080227

Deciphering Single Nucleotide Polymorphisms and Evolutionary Trends in Isolates of the Cydia pomonella granulovirus

2017· article· en· W2747867354 on OpenAlexaboutno aff
Jörg T. Wennmann, Pit Radtke, Karolin Eberle, Gianpiero Gueli Alletti, Johannes A. Jehle

Bibliographic record

VenueViruses · 2017
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicViral Infectious Diseases and Gene Expression in Insects
Canadian institutionsnot available
Fundersnot available
KeywordsBiologyGenomeGeneticsGene

Abstract

fetched live from OpenAlex

Six complete genome sequences of Cydia pomonella granulovirus (CpGV) isolates from Mexico (CpGV-M and CpGV-M1), England (CpGV-E2), Iran (CpGV-I07 and CpGV-I12), and Canada (CpGV-S) were aligned and analyzed for genetic diversity and evolutionary processes. The selected CpGV isolates represented recently identified phylogenetic lineages of CpGV, namely, the genome groups A to E. The genomes ranged from 120,816 bp to 124,269 bp. Several common differences between CpGV-M, -E2, -I07, -I12 and -S to CpGV-M1, the first sequenced and published CpGV isolate, were highlighted. Phylogenetic analysis based on the aligned genome sequences grouped CpGV-M and CpGV-I12 as the most derived lineages, followed by CpGV-E2, CpGV-S and CpGV-I07, which represent the most basal lineages. All of the genomes shared a high degree of co-linearity, with a common setup of 137 (CpGV-I07) to 142 (CpGV-M and -I12) open reading frames with no translocations. An overall trend of increasing genome size and a decrease in GC content was observed, from the most basal lineage (CpGV-I07) to the most derived (CpGV-I12). A total number of 788 positions of single nucleotide polymorphisms (SNPs) were determined and used to create a genome-wide SNP map of CpGV. Of the total amount of SNPs, 534 positions were specific for exactly one of either isolate CpGV-M, -E2, -I07, -I12 or -S, which allowed the SNP-based detection and identification of all known CpGV isolates.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.337
Threshold uncertainty score0.312

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
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 head0.020
GPT teacher head0.270
Teacher spread0.250 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
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

Citations22
Published2017
Admission routes1
Has abstractyes

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