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Record W2064233244 · doi:10.3390/v1020084

Molecular Characterization of Viruses from Clinical Respiratory Samples Producing Unidentified Cytopathic Effects in Cell Culture

2009· article· en· W2064233244 on OpenAlexaff
Yacine Abed, Guy Boivin

Bibliographic record

VenueViruses · 2009
Typearticle
Languageen
FieldMedicine
TopicRespiratory viral infections research
Canadian institutionsUniversité Laval
Fundersnot available
KeywordsVirologyBiologyCytopathic effectVirusPrimer (cosmetics)AmpliconSequence analysisViral culturePolymerase chain reactionSequence (biology)GeneticsGeneChemistry

Abstract

fetched live from OpenAlex

The sequence-independent single primer amplification (SISPA) method was performed to identify a virus in 17 clinical respiratory samples producing uncharacterized cytopathic effects in LLC-MK2 cells. Sequence analysis of 600-1600 bp amplicons allowed the identification of six viruses (one influenza C, two parechovirus-3 and three cardioviruses). Genomic sequences of the cardioviruses showed similarities with those of the recently-described Saffold virus strain although significant variation was present in the viral surface EF and CD loops. These results demonstrate the usefulness of SISPA for identifying emerging viruses and also known viruses not easily identified by standard virological methods.

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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.002

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
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 integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.094
GPT teacher head0.400
Teacher spread0.306 · 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
Published2009
Admission routes1
Has abstractyes

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