Xenbase: a Xenopus biology and genomics resource
Bibliographic record
Abstract
Xenbase (www.xenbase.org) is a model organism database integrating a diverse array of biological and genomic data on the frogs, Xenopus laevis and Xenopus (Silurana) tropicalis. Data is collected from other databases, high-throughput screens and the scientific literature and integrated into a number of database modules covering subjects such as community, literature, gene and genomic analysis. Gene pages are automatically assembled from data piped from the Entrez Gene, Gurdon Institute, JGI, Metazome, MGI, OMIM, PubMed, Unigene, Zfin, commercial suppliers and others. These data are then supplemented with in-house annotation. Xenbase has implemented the Gbrowse genome browser and also provides a BLAST service that allows users to specifically search either laevis or tropicalis DNA or protein targets. A table of Xenopus gene synonyms has been implemented and allows the genome, genes, publications and high-throughput gene expression data to be seamlessly integrated with other Xenopus data and to external database resources, making the wealth of developmental and functional data from the frog available to the broader research community.
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 imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.005 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.043 | 0.032 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".