A compilation of molecular biology web servers: 2006 update on the Bioinformatics Links Directory
Bibliographic record
Abstract
The Bioinformatics Links Directory is a public online resource that lists the servers published in this and all previously published Nucleic Acids Research Web Server issues together with other useful tools, databases and resources for bioinformatics and molecular biology research. This rich directory of tools and websites can be browsed and searched with all listed links freely accessible to the public. The 2006 update includes the 149 websites highlighted in the July 2006 issue of Nucleic Acids Research and brings the total number of servers listed in the Bioinformatics Links Directory to over 1000 links. To aid navigation through this growing resource, all link entries contain a brief synopsis, a citation list and are classified by function in descriptive biological categories. The most up-to-date version of this actively maintained listing of bioinformatics resources is available at the Bioinformatics Links Directory website, http://bioinformatics.ubc.ca/resources/links_directory/. A complete list of all links listed in this Nucleic Acids Research 2006 Web Server issue can be accessed online at http://bioinformatics.ubc.ca/resources/links_directory/narweb2006/. The 2006 update of the Bioinformatics Links Directory, which includes the Web Server list and summaries, is also available online at the Nucleic Acids Research website, http://nar.oupjournals.org/.
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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 | 0.010 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.007 | 0.011 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.007 | 0.005 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.001 | 0.005 |
| Insufficient payload (model declined to judge) | 0.078 | 0.269 |
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".