The UCSC Archaeal Genome Browser: 2012 update
Bibliographic record
Abstract
The UCSC Archaeal Genome Browser (http://archaea.ucsc.edu) offers a graphical web-based resource for exploration and discovery within archaeal and other selected microbial genomes. By bringing together existing gene annotations, gene expression data, multiple-genome alignments, pre-computed sequence comparisons and other specialized analysis tracks, the genome browser is a powerful aggregator of varied genomic information. The genome browser environment maintains the current look-and-feel of the vertebrate UCSC Genome Browser, but also integrates archaeal and bacterial-specific tracks with a few graphic display enhancements. The browser currently contains 115 archaeal genomes, plus 31 genomes of viruses known to infect archaea. Some of the recently developed or enhanced tracks visualize data from published high-throughput RNA-sequencing studies, the NCBI Conserved Domain Database, sequences from pre-genome sequencing studies, predicted gene boundaries from three different protein gene prediction algorithms, tRNAscan-SE gene predictions with RNA secondary structures and CRISPR locus predictions. We have also developed a companion resource, the Archaeal COG Browser, to provide better search and display of arCOG gene function classifications, including their phylogenetic distribution among available archaeal genomes.
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 | 0.004 | 0.007 |
| Meta-epidemiology (narrow) | 0.003 | 0.003 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.007 | 0.010 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.005 | 0.005 |
| Open science | 0.005 | 0.003 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.038 | 0.074 |
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".