Providing web servers and training in Bioinformatics: 2010 update on the Bioinformatics Links Directory
Bibliographic record
Abstract
The Links Directory at Bioinformatics.ca continues its collaboration with Nucleic Acids Research to jointly publish and compile a freely accessible, online collection of tools, databases and resource materials for bioinformatics and molecular biology research. The July 2010 Web Server issue of Nucleic Acids Research adds an additional 115 web server tools and 7 updates to the directory at http://bioinformatics.ca/links_directory/, bringing the total number of servers listed close to an impressive 1500 links. The Bioinformatics Links Directory represents an excellent community resource for locating bioinformatic tools and databases to aid one's research, and in this context bioinformatic education needs and initiatives are discussed. A complete list of all links featured in this Nucleic Acids Research 2010 Web Server issue can be accessed online at http://bioinformatics.ca/links_directory/narweb2010/. The 2010 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.oxfordjournals.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 | 0.014 | 0.036 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.011 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.005 | 0.010 |
| Open science | 0.004 | 0.005 |
| Research integrity | 0.003 | 0.006 |
| Insufficient payload (model declined to judge) | 0.057 | 0.124 |
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".