Bibliographic record
Abstract
The organelle genome database GOBASE is now in its twelfth release, and includes 350,000 mitochondrial sequences and 118,000 chloroplast sequences, roughly a 3-fold expansion since previously documented. GOBASE also includes a fully reannotated genome sequence of Rickettsia prowazekii, one of the closest bacterial relatives of mitochondria, and will shortly expand to contain more data from bacteria from which organelles originated. All these sequences are now accessible through a single unified interface. Enhancements to the functionality of GOBASE include addition of pages for RNA structures and a page compiling data about the taxonomic distribution of organelle-encoded genes; incorporation of Gene Ontology terms; addition of features deduced from incomplete annotations to sequences in GenBank; marking of type examples in cases where single genes in single species are oversampled within GenBank; and addition of graphics illustrating gene structure and the position of neighbouring genes on a sequence. The database has been reimplemented in PostgreSQL to facilitate development and maintenance, and structural modifications have been made to speed up queries, particularly those related to taxonomy. The GOBASE database can be queried at http://gobase.bcm.umontreal.ca/ and inquiries should be directed to gobase@bch.umontreal.ca.
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 | 0.003 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.011 | 0.013 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.028 | 0.037 |
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".