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Record W4393950665 · doi:10.1093/genetics/iyae050

WormBase 2024: status and transitioning to Alliance infrastructure

2024· article· en· W4393950665 on OpenAlexaff
Paul W. Sternberg, Kimberly Van Auken, Qinghua Wang, Adam Wright, Karen Yook, Magdalena Zarowiecki, Valerio Arnaboldi, Andrés Becerra, Stephanie Brown, Scott Cain, Juancarlos Chan, Wen J. Chen, Jaehyoung Cho, Paul A. Davis, Stavros Diamantakis, Sarah Dyer, Dionysios Grigoriadis, Christian A Grove, Todd Harris, Kevin Howe, Ranjana Kishore, Raymond Lee, Ian Longden, Manuel Luypaert, Hans‐Michael Müller, Paulo Nuin, Mark Quinton-Tulloch, Daniela Raciti, Tim Schedl, Gary Schindelman, Lincoln Stein

Bibliographic record

VenueGenetics · 2024
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicGenetics, Aging, and Longevity in Model Organisms
Canadian institutionsOntario Institute for Cancer Research
FundersU.S. National Library of MedicineNational Human Genome Research InstituteNational Heart, Lung, and Blood InstituteMedical Research Council
KeywordsAllianceCaenorhabditis elegansBiologyGenomeState (computer science)Key (lock)Knowledge managementGeneticsComputational biologyData sciencePolitical scienceGeneEcologyComputer science

Abstract

fetched live from OpenAlex

WormBase has been the major repository and knowledgebase of information about the genome and genetics of Caenorhabditis elegans and other nematodes of experimental interest for over 2 decades. We have 3 goals: to keep current with the fast-paced C. elegans research, to provide better integration with other resources, and to be sustainable. Here, we discuss the current state of WormBase as well as progress and plans for moving core WormBase infrastructure to the Alliance of Genome Resources (the Alliance). As an Alliance member, WormBase will continue to interact with the C. elegans community, develop new features as needed, and curate key information from the literature and large-scale projects.

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)0.039
metaresearch head score (Gemma)0.067
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesScholarly communication
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.989
Threshold uncertainty score0.207

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0390.067
Meta-epidemiology (narrow)0.0020.002
Meta-epidemiology (broad)0.0030.002
Bibliometrics0.0090.011
Science and technology studies0.0030.002
Scholarly communication0.0110.024
Open science0.0110.017
Research integrity0.0050.007
Insufficient payload (model declined to judge)0.0310.065

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 head0.006
GPT teacher head0.236
Teacher spread0.230 · 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.

Study designNot applicable
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

Citations275
Published2024
Admission routes1
Has abstractyes

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