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Record W2322138869 · doi:10.1371/currents.rrn1040

SeqMonitor: Influenza Analysis Pipeline and Visualization

2009· article· en· W2322138869 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenuePLoS Currents · 2009
Typearticle
Languageen
FieldMedicine
TopicInfluenza Virus Research Studies
Canadian institutionsDalhousie University
FundersGenome AtlanticKillam TrustsNatural Sciences and Engineering Research Council of CanadaCanada Research Chairs
KeywordsMetadataUploadGenBankComputer scienceWorld Wide WebVisualizationPipeline (software)Data scienceData miningBiologyGenetics

Abstract

fetched live from OpenAlex

Unprecedented sequencing effort has led to daily submissions of influenza genomes to public repositories such as the NCBI GenBank. With the decreasing cost of genome sequencing, it is expected that rapidly evolving viruses such as influenza will be sampled in even greater depth in the future. Keeping analyses up to date and managing this data is a prime concern for researchers and public-health officials alike. We have developed an influenza sequence pipeline, polymorphism data warehouse, and an interactive web-based analysis program to assist in managing the flow of sequence data. The system provides a framework for studying polymorphic associations with various metadata, for downloading subsets based on metadata criteria, as well as for tracking polymorphisms geographically and temporally. SeqMonitor is accessible at http://ratite.cs.dal.ca/SeqMonitor. Systems recently developed and under development are allowing the quick identification of important, novel mutations using 3-d protein structures [5] , as well as H3N2 antigenic-site-based vaccine prediction systems ( http://influenza.nhri.org.tw/ATIVS/index.jsp ) [6] . This type of automated detection and monitoring of novel mutations affecting antigenicity, convergent evolution, and inter/intra-host reassortment needs to be performed on a continual basis on the everincreasing dataset to keep abreast of new influenza threats. To this end, we have created an automated pipeline that can download the latest sequences from NCBI GenBank and add them to existing alignments of homologous sequences, as well as extract metadata such as antiviral resistance, collection date and location name. Each sequence can then be geotagged by an automated, user-verified extraction and querying engine which uses the GeoNames web service ( http://www.geonames.org ). The data are made available through our data warehouse and web application, SeqMonitor. The current version of SeqMonitor allows users to submit H1N1 protein sequences of the hemagglutinin or neuraminidase genes to a BLAST query, with the top matches being plotted on a geographic map. Novel and rare mutations of the query sequence can then be analyzed versus any subset of the data, defined for instance by oseltamivir resistance or country of collection. The geographic and related metadata files, along with the precomputed amino acid alignments constructed with the pipeline can be downloaded by users and processed by geographic and sequence data analysis packages such as GenGIS ( http://kiwi.cs.dal.ca/GenGIS ) [7][8] . SeqMonitor can be accessed at http://ratite.cs.dal.ca/SeqMonitor .

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.

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.034
Threshold uncertainty score0.466

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.120
GPT teacher head0.442
Teacher spread0.322 · 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