Bibliographic record
Abstract
The American Society for Information Science and Technology’s SIG for International Information Issues’ fundraising raffle for this year’s international paper contest is in full swing. The grand-prize winner will go home with a sophisticated Dell Inspiron Digital Notebook. The fundraiser kicked off on April 1, 2007, and will conclude with a draw during the 2007 International Reception at the ASIST Annual Meeting in Milwaukee, Wisconsin in October 2007. Only 250 tickets will be sold, thus each entrant has an excellent chance of winning the grand prize. Tickets are sold on a first come, first served basis. Monies raised will promote international research by benefiting the winners of the 2007 international paper contest. Tickets are available at: http://www.asist.org/SIG/SIGIII/fundraising/fundraising2007/ The purposes of SIG III are: to promote better awareness among ASIST members and information professionals of the importance of international cooperation to facilitate and enhance better communication and interaction among ASIST members and their foreign colleagues on information issues to develop an international network of digital scholars and experts on digital libraries and information technology in developing countries to provide a forum for exploring and discussing international information issues and problems SIG III membership includes most non-U.S. ASIST members, and a true cross-section of U.S. ASIST members. More information about the paper contest can be found on the award winning SIG III website under Paper Contest: http://www.asis.org/SIG/SIGIII/index.htm
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 | 0.006 | 0.006 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.005 | 0.001 |
| Scholarly communication | 0.015 | 0.003 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.005 | 0.006 |
| Insufficient payload (model declined to judge) | 0.308 | 0.296 |
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".