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Record W2163673721 · doi:10.1002/jmv.10145

Foodborne outbreak caused by a Norwalk‐like virus in India

2002· article· en· W2163673721 on OpenAlexaboutno aff
Shobha Broor, Lalit Dar, D. Ghosh

Bibliographic record

VenueJournal of Medical Virology · 2002
Typearticle
Languageen
FieldMedicine
TopicViral gastroenteritis research and epidemiology
Canadian institutionsnot available
Fundersnot available
KeywordsOutbreakVirologyImmunoelectron microscopyAmpliconBiologyRotavirusVirusPolymerase chain reactionCaliciviridaeMicrobiologyGeneNorovirusAntibodyGenetics

Abstract

fetched live from OpenAlex

An outbreak of acute gastroenteritis occurred in the nurses' hostel of a civil hospital in Delhi, after a farewell party involving 130 nurses and some of the housekeeping staff. All affected persons had eaten salad sandwiches at the party. Stool samples were collected from six of these patients on the second day of infection. All six samples, when tested for the presence of common bacteria, parasites, and rotavirus, were found to be negative. The clinical features of this outbreak matched the criteria set for outbreaks caused by Norwalk-like viruses (NLVs). Reverse transcription-polymerase chain reaction (RT-PCR) was carried out on these six samples, using primers from the RNA-dependent RNA polymerase (RdRp) gene of NLVs. Immunoelectron microscopy was carried out on two of the samples, using convalescent phase serum. All six samples were positive for genogroup (GG) II NLVs by RT-nested PCR. Aggregates of 32-nm viral particles were visualized by immunoelectron microscopy in one of the two samples. Sequencing of the RdRp gene was done on amplicons from three samples; phylogenetic analysis placed the isolates NDV/1999 in a Toronto virus cluster of GG II NLVs. This is the first report of a food-borne outbreak attributable to NLVs from India.

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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.013
Threshold uncertainty score0.027

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0020.001
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0010.001
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 head0.027
GPT teacher head0.318
Teacher spread0.291 · 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

Citations54
Published2002
Admission routes1
Has abstractyes

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