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Record W2147119862 · doi:10.1093/database/bar031

The Reactome BioMart

2011· article· pt· W2147119862 on OpenAlexaff
Robin Haw, David Croft, Christina K. Yung, Nelson Ndegwa, Peter D’Eustachio, Henning Hermjakob, Lincoln Stein

Bibliographic record

VenueDatabase · 2011
Typearticle
Languagept
FieldBiochemistry, Genetics and Molecular Biology
TopicBioinformatics and Genomic Networks
Canadian institutionsOntario Institute for Cancer Research
FundersNational Human Genome Research InstituteNational Institutes of HealthEuropean Commission
KeywordsComputer scienceSuiteInterface (matter)Information retrievalUser interfaceWorld Wide WebSimple (philosophy)DatabaseProgramming language

Abstract

fetched live from OpenAlex

Reactome is an open source, expert-authored, manually curated and peer-reviewed database of reactions, pathways and biological processes. We provide an intuitive web-based user interface to pathway knowledge and a suite of data analysis tools. The Reactome BioMart provides biologists and bioinformaticians with a single web interface for performing simple or elaborate queries of the Reactome database, aggregating data from different sources and providing an opportunity to integrate experimental and computational results with information relating to biological pathways. Database URL: http://www.reactome.org.

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)0.006
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 score0.042
Threshold uncertainty score0.141

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.006
Meta-epidemiology (narrow)0.0040.002
Meta-epidemiology (broad)0.0040.003
Bibliometrics0.0050.003
Science and technology studies0.0010.001
Scholarly communication0.0040.002
Open science0.0050.004
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0420.054

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 head0.026
GPT teacher head0.240
Teacher spread0.214 · 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

Citations38
Published2011
Admission routes1
Has abstractyes

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