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Record W2336957559 · doi:10.1186/s13059-016-0924-1

JBrowse: a dynamic web platform for genome visualization and analysis

2016· article· en· W2336957559 on OpenAlexafffund
Robert Buels, Eric Yao, Colin Diesh, Richard D. Hayes, Mónica Muñoz-Torres, Gregg Helt, David Goodstein, Christine G. Elsik, Suzanna Lewis, Lincoln Stein, Ian Holmes

Bibliographic record

VenueGenome biology · 2016
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicGenetics, Bioinformatics, and Biomedical Research
Canadian institutionsInstitute of Cancer ResearchUniversity of TorontoOntario Institute for Cancer Research
FundersNational Institute of General Medical SciencesNational Human Genome Research InstituteUniversity of Waterloo
KeywordsPlug-inVisualizationHTML5JavaScriptComputer scienceAnnotationWeb applicationScalabilityGenome browserWorld Wide WebGenomeInteractive visualizationInformation retrievalBiologyGenomicsData miningDatabaseOperating systemArtificial intelligenceGenetics

Abstract

fetched live from OpenAlex

BACKGROUND: JBrowse is a fast and full-featured genome browser built with JavaScript and HTML5. It is easily embedded into websites or apps but can also be served as a standalone web page. RESULTS: Overall improvements to speed and scalability are accompanied by specific enhancements that support complex interactive queries on large track sets. Analysis functions can readily be added using the plugin framework; most visual aspects of tracks can also be customized, along with clicks, mouseovers, menus, and popup boxes. JBrowse can also be used to browse local annotation files offline and to generate high-resolution figures for publication. CONCLUSIONS: JBrowse is a mature web application suitable for genome visualization and analysis.

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)0.007
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 score0.072
Threshold uncertainty score0.241

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.007
Meta-epidemiology (narrow)0.0030.003
Meta-epidemiology (broad)0.0020.002
Bibliometrics0.0060.003
Science and technology studies0.0010.001
Scholarly communication0.0050.004
Open science0.0050.005
Research integrity0.0020.006
Insufficient payload (model declined to judge)0.0720.085

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 head0.015
GPT teacher head0.304
Teacher spread0.289 · 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

Citations842
Published2016
Admission routes2
Has abstractyes

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