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Record W2138453085 · doi:10.1093/bioinformatics/bts430

Gemma: a resource for the reuse, sharing and meta-analysis of expression profiling data

2012· article· en· W2138453085 on OpenAlexafffund
Anton Zoubarev, Kelsey M. Hamer, Kiran Keshav, Erin McCarthy, Joseph Roy C. Santos, Thea Van Rossum, Cameron J. McDonald, Adam Hall, Xiang Wan, Raymond S. Lim, Jesse Gillis, Paul Pavlidis

Bibliographic record

VenueBioinformatics · 2012
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicGene expression and cancer classification
Canadian institutionsUniversity of British Columbia
FundersNational Institute of General Medical SciencesCanadian Institutes of Health ResearchNational Institutes of HealthMichael Smith Health Research BC
KeywordsComputer scienceLicenseGemmaProfiling (computer programming)Plug-inSoftwareWorld Wide WebData scienceDatabaseInformation retrievalBiologyOperating system

Abstract

fetched live from OpenAlex

UNLABELLED: Gemma is a database, analysis software system and web site for genomics data re-use and meta-analysis. Currently, Gemma contains analyzed data from over 3300 expression profiling studies, yielding hundreds of millions of differential expression results and coexpression patterns (correlated expression) for retrieval and visualization. With optional registration users can save their own data and securely share it with other users. Web services and integration with third-party resources further increase the scope of the tools, which include a Cytoscape plugin. AVAILABILITY: http://chibi.ubc.ca/Gemma, Apache 2.0 license.

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)0.011
metaresearch head score (Gemma)0.018
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesOpen science
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 score0.993
Threshold uncertainty score0.070

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0110.018
Meta-epidemiology (narrow)0.0030.002
Meta-epidemiology (broad)0.0030.003
Bibliometrics0.0090.008
Science and technology studies0.0010.001
Scholarly communication0.0040.005
Open science0.0070.006
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0210.017

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 head0.154
GPT teacher head0.340
Teacher spread0.186 · 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
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

Citations158
Published2012
Admission routes2
Has abstractyes

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