International Association of Technological University Libraries (IATUL) 2005 Meeting
Bibliographic record
Abstract
Purpose Aims to report on the 26th IATUL Annual Conference. Design/methodology/approach The conference focused on three major themes: infrastructure, people and global innovation initiatives, which are summarised. Findings This conference addressed many important and relevant issues to science and technological universities worldwide. Collaboration, partnership and further discussion not only within IATUL membership but with members of other organizations such as IFLA can further enhance the mission information dissemination of technological libraries. The conference highlighted several important issues that the information professionals worldwide need to continue to think, reflect and develop strategies to practically implement them for the benefit to not only to the information producing and disseminating organizations but the society as a whole. Originality/value This conference provided ample opportunities to network with information experts in a variety of specialty areas such as Open Access Initiative, Scholarly communication, Digital Libraries and Information Literacy, etc. The networking opportunities provided further opportunities to collaborate and in the process create future opportunities to enhance mission of technological libraries to fulfill information needs of their researchers and scientists in the most efficient ways. The value gained is enormous and recommend future dialogs and interaction by IATUL with other organizations such as IFLA.
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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 | 0.012 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.006 |
| Science and technology studies | 0.008 | 0.001 |
| Scholarly communication | 0.019 | 0.004 |
| Open science | 0.002 | 0.008 |
| Research integrity | 0.005 | 0.003 |
| Insufficient payload (model declined to judge) | 0.143 | 0.066 |
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".