Bluejay: A Highly Scalable and Integrative Visual Environment for Genome Exploration
Bibliographic record
Abstract
Many questions that biologists want to answer using the information available from completely sequenced genomes are complex. A graphical environment allows users to visually explore and operate on a sequence. Sequence and annotation data exists in bewildering varieties of types and levels of detail. The graphical environment therefore needs to adapt to this variation to provide the user the best possible visual representation of genomic data in a given context. As more and more online tools and services become available for biologists, mediating software should also be able to integrate and link to them. The Bluejay browser is a Java-based visual environment for exploring biological sequences. Uniquely, Bluejay fully integrates existing gene expression software into a genomic context. Bluejay also differentiates itself from most form-based HTML sequence browsers because it: (i) is highly scalable so that it can visualize a wide range of genomic objects ranging from a large whole genome down to individual nucleotides by using data-transformational Web services; and (ii) dynamically discovers and provides links to disparate resources such as gene annotation data (via XLinks) and semantically- described biological Web Services (via the BioMOBY protocol).
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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.005 |
| Open science | 0.004 | 0.006 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.043 | 0.022 |
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".