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Record W2765797013 · doi:10.1093/nar/gkx936

Xenbase: a genomic, epigenomic and transcriptomic model organism database

2017· article· en· W2765797013 on OpenAlex
Kamran Karimi, Joshua D. Fortriede, Vaneet Lotay, Kevin A. Burns, Dong Zhou Wang, Malcolm E Fisher, Troy J. Pells, Christina James‐Zorn, Ying Wang, Virgilio Ponferrada, Stanley Chu, Praneet Chaturvedi, Aaron M. Zorn, Peter D. Vize

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueNucleic Acids Research · 2017
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicGenomics and Phylogenetic Studies
Canadian institutionsUniversity of Calgary
FundersEunice Kennedy Shriver National Institute of Child Health and Human DevelopmentNational Institutes of HealthWellcome Trust
KeywordsBiologyGenome browserGenomeEpigenomicsComputational biologyChromosome conformation captureGenomicsVisualizationDatabaseGeneticsComputer scienceDNA methylationGeneData mining

Abstract

fetched live from OpenAlex

Xenbase (www.xenbase.org) is an online resource for researchers utilizing Xenopus laevis and Xenopus tropicalis, and for biomedical scientists seeking access to data generated with these model systems. Content is aggregated from a variety of external resources and also generated by in-house curation of scientific literature and bioinformatic analyses. Over the past two years many new types of content have been added along with new tools and functionalities to reflect the impact of high-throughput sequencing. These include new genomes for both supported species (each with chromosome scale assemblies), new genome annotations, genome segmentation, dynamic and interactive visualization for RNA-Seq data, updated ChIP-Seq mapping, GO terms, protein interaction data, ORFeome support, and improved connectivity to other biomedical and bioinformatic resources.

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.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.371
Threshold uncertainty score0.863

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.059
GPT teacher head0.336
Teacher spread0.277 · 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