GOBASE: an organelle genome database
Bibliographic record
Abstract
The organelle genome database GOBASE, now in its 21st release (June 2008), contains all published mitochondrion-encoded sequences (approximately 913,000) and chloroplast-encoded sequences (approximately 250,000) from a wide range of eukaryotic taxa. For all sequences, information on related genes, exons, introns, gene products and taxonomy is available, as well as selected genome maps and RNA secondary structures. Recent major enhancements to database functionality include: (i) addition of an interface for RNA editing data, with substitutions, insertions and deletions displayed using multiple alignments; (ii) addition of medically relevant information, such as haplotypes, SNPs and associated disease states, to human mitochondrial sequence data; (iii) addition of fully reannotated genome sequences for Escherichia coli and Nostoc sp., for reference and comparison; and (iv) a number of interface enhancements, such as the availability of both genomic and gene-coding sequence downloads, and a more sophisticated literature reference search functionality with links to PubMed where available. Future projects include the transfer of GOBASE features to NCBI/GenBank, allowing long-term preservation of accumulated expert information. The GOBASE database can be found at http://gobase.bcm.umontreal.ca/. Queries about custom and large-scale data retrievals should be addressed 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 | 0.009 | 0.010 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.004 | 0.003 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.029 | 0.042 |
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".