Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
The 2008 Web Server Issue of Nucleic Acids Research is the sixth in a series of annual special issues dedicated to web-based software resources for analysis of molecular biology data. It is freely available online under NAR' s open access policy and print copies are available for separate purchase. The present issue reports on 94 web servers. A handful of these are updates to existing software, but the overwhelming majority are new resources. The distribution of topics provides a snapshot of challenging problems in computational biology. RNA, DNA and genomes are the focus of a quarter of the papers. Proteins are the subject of another quarter. This year we have had a special emphasis on resources for molecular network and pathway analysis and biological text mining. Thirteen of the papers fall in these categories and an additional 14 papers involve data or analyses that precede or work in conjunction with network analysis, including microarray data and gene set enrichment analysis. The remainder of the papers constitute a mix of topics including phylogenomics, mass spectroscopy and NMR and computational immunomics. The scientists and programmers who have provided us with these resources deserve our immense thanks. They epitomize the scientific spirit of work shared for the benefit of all. Also included in the present issue is the Bioinformatics Links Directory 2008 update by Michelle Brazas, Francis Ouellette and their colleagues at the Ontario Institute for Cancer Research. The directory, at http://bioinformatics.ca/links_directory , is a searchable compilation of web servers published in this and previous Web Server issues together with other useful tools, databases and resources for life sciences research. I would like to thank these authors for their tireless work for the community. The Web Server issue would not be possible without the conscientious efforts of literally hundreds of reviewers. Thanks to you all. My work was made immeasurably easier by the dedicated editorial assistance of Fay Oppenheim. Thank you. Thanks also to Karen Otto of NAR and the staff at Oxford University Press for their invaluable assistance. For the 2009 Web Server issue, we will add metagenomics to the continuing special focus on network and pathway analysis and biological text mining. Of course, topics more generally related to DNA, RNA and proteins are welcome. Authors wishing to submit manuscripts for the 2009 Web Server issue must contact me at narwbsrv@bu.edu to check the suitability of their proposed submission by 31 December 2008 at the latest. A maximum one page summary of the web server function, along with the URL address of the fully functional website, should be submitted for this purpose. Detailed instructions and requirements are presented at http://www.oxfordjournals.org/nar/for_authors/submission_webserver.html and this information should be consulted before sending in the summary. The deadline for submission of articles is 31 January 2009.
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.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.005 | 0.013 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.004 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.004 | 0.004 |
| Research integrity | 0.007 | 0.006 |
| Insufficient payload (model declined to judge) | 0.001 | 0.004 |
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 it