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Record W3158822542 · doi:10.3390/microorganisms9050955

Comparison of Molecular and In Silico Salmonella Serotyping for Salmonella Surveillance

2021· article· en· W3158822542 on OpenAlexaffabout
Linda Chui, Christina Ferrato, Vincent Li, Sara Christianson

Bibliographic record

VenueMicroorganisms · 2021
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicSalmonella and Campylobacter epidemiology
Canadian institutionsPublic Health Agency of CanadaProvincial Laboratory of Public HealthUniversity of Alberta
Fundersnot available
KeywordsSalmonellaSerotypeIn silicoBiologyMicroarrayTypingDNA microarrayDNA sequencingOutbreakWhole genome sequencingGenomeMultilocus sequence typingComputational biologyMicrobiologyVirologyGeneticsDNAGeneBacteriaGenotype

Abstract

fetched live from OpenAlex

Salmonella surveillance and outbreak management is a key function of public health. Laboratories are shifting from antigenic serotype determination to molecular methods including microarray or whole genome sequencing technologies. The objective of this study was to compare the Check&Trace Salmonella™ DNA microarray (CTS), a commercially available assay with the Salmonella in silico typing resource (SISTR), which uses whole genome sequencing technology for serotyping clinical Salmonella strains in Alberta, Canada, collected over an 18-month period. A high proportion of isolates (96.3%) were successfully typed by both systems. SISTR is a powerful tool for laboratories which already have a WGS infrastructure in place, whereas smaller laboratories can benefit from a commercial microarray system and reduce the processing cost per isolate compared to traditional serotyping.

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 score0.089
Threshold uncertainty score0.301

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 head0.027
GPT teacher head0.282
Teacher spread0.255 · 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

Citations13
Published2021
Admission routes2
Has abstractyes

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