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Record W2112466127 · doi:10.1093/nar/gkp952

WormBase: a comprehensive resource for nematode research

2009· article· en· W2112466127 on OpenAlexaff
Todd Harris, Igor Antoshechkin, Tamberlyn Bieri, Darin Blasiar, Juancarlos Chan, Wen J. Chen, Norie De La Cruz, Paul A. Davis, Margaret Duesbury, Ruihua Fang, Jolene S. Fernandes, Michael Han, Ranjana Kishore, Raymond Lee, Hans‐Michael Müller, Cecilia Nakamura, Philip Ozersky, Petcherski Andrei, Arun Rangarajan, Anthony S. Rogers, Gary Schindelman, Erich M. Schwarz, Mary Ann Tuli, Kimberly Van Auken, Daniel Wang, Xiaodong Wang, Gary W. Williams, Karen Yook, Richard Durbin, Lincoln Stein, John Spieth, Paul W. Sternberg

Bibliographic record

VenueNucleic Acids Research · 2009
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicGenetics, Aging, and Longevity in Model Organisms
Canadian institutionsOntario Institute for Cancer Research
FundersMedical Research CouncilNational Institutes of HealthNational Human Genome Research InstituteHoward Hughes Medical Institute
KeywordsBiologyCaenorhabditis elegansPipeline (software)GenomeResource (disambiguation)Function (biology)Computational biologyCaenorhabditisGeneService (business)GenomicsData scienceGeneticsComputer science

Abstract

fetched live from OpenAlex

WormBase (http://www.wormbase.org) is a central data repository for nematode biology. Initially created as a service to the Caenorhabditis elegans research field, WormBase has evolved into a powerful research tool in its own right. In the past 2 years, we expanded WormBase to include the complete genomic sequence, gene predictions and orthology assignments from a range of related nematodes. This comparative data enrich the C. elegans data with improved gene predictions and a better understanding of gene function. In turn, they bring the wealth of experimental knowledge of C. elegans to other systems of medical and agricultural importance. Here, we describe new species and data types now available at WormBase. In addition, we detail enhancements to our curatorial pipeline and website infrastructure to accommodate new genomes and an extensive user base.

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)0.003
metaresearch head score (Gemma)0.008
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: none
Teacher disagreement score0.049
Threshold uncertainty score0.164

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.008
Meta-epidemiology (narrow)0.0030.002
Meta-epidemiology (broad)0.0030.001
Bibliometrics0.0130.013
Science and technology studies0.0020.001
Scholarly communication0.0040.005
Open science0.0050.004
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0490.068

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 head0.085
GPT teacher head0.391
Teacher spread0.306 · 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

Citations379
Published2009
Admission routes1
Has abstractyes

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