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Record W4391220908 · doi:10.1099/acmi.0.000742.v3

BactEXTRACT: an R Shiny app to quickly extract, plot and analyse bacterial growth and gene expression data

2024· article· en· W4391220908 on OpenAlexaff
Julien Dénéréaz, Jan‐Willem Veening

Bibliographic record

VenueAccess Microbiology · 2024
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicGene expression and cancer classification
Canadian institutionsRoyal College of Physicians and Surgeons of Canada
FundersSchweizerischer Nationalfonds zur Förderung der Wissenschaftlichen ForschungNational Science Foundation
KeywordsPlot (graphics)Interface (matter)Gene expressionExpression (computer science)GeneComputer graphics (images)VisualizationRaw dataComputer scienceComputational biologyR packageData miningBiologyBiological systemGeneticsMathematicsOperating systemComputational scienceStatisticsProgramming language

Abstract

fetched live from OpenAlex

To streamline the analysis and visualization of bacterial growth and gene expression data obtained by microtitre plate readers, we developed BactEXTRACT, an intuitive, easy-to-use R Shiny application. BactEXTRACT simplifies the transition from raw optical density, fluorescence and luminescence measurements to publication-ready plots. This package offers a user-friendly interface that reduces the complexity involved in growth curve and gene expression analysis and is generally applicable. BactEXTRACT is available at https://veeninglab.com/bactextract.

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)0.004
metaresearch head score (Gemma)0.013
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Software · Consensus signal: Software
Teacher disagreement score0.151
Threshold uncertainty score0.504

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.013
Meta-epidemiology (narrow)0.0040.003
Meta-epidemiology (broad)0.0030.002
Bibliometrics0.0050.003
Science and technology studies0.0010.001
Scholarly communication0.0030.003
Open science0.0040.003
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.1510.169

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 head0.034
GPT teacher head0.328
Teacher spread0.294 · 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 designNot applicable
Domainnot available
GenreSoftware

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

Citations15
Published2024
Admission routes1
Has abstractyes

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