IFLA Health and Biosciences Libraries Section: Call for Papers for Satellite Session
Bibliographic record
Abstract
Role of Evidence-based Research in Medical Libraries The one-day session will have two sub-themes: 1. Library efforts in support of evidence-based research. 2. Research conducted by health science libraries and librarians. The audience of this session is likely to include health care professionals, educators, researchers and librarians. You are invited to submit an abstract for one of the two themes. It is hoped that papers will cover a wide range of areas, for example: How libraries train library staff and users in using evidence. Partnerships and collaborations that support evidence-based research. Research that has made a difference to library services. The librarian’s role in critical appraisal of the evidence. Clinical librarians - walking the talk. Tools to support evidence-based medicine. Research methods. Promoting the evidence. Presentations are suggested to be no more than 30 minutes, including 10 minutes for questions. Submission Guidelines: The proposals must be submitted in an electronic format and must contain: title of paper; summary of paper (250 - 350 words maximum); speaker's name, address, telephone and fax numbers, professional affiliation, email address, and biographical note (40 words maximum). Submissions must be received no later than December 24th, 2007, preferably by email to: Heather Todd University of Queensland Library St Lucia campus St Lucia, Queensland 4072 E-mail: h.todd@library.uq.edu.au Important dates: Satellite Session (preceding the IFLA Conference): August 10th-14th, 2008 Quebec City, Quebec, Canada Deadline for submission of abstracts: December 24th, 2007: Notification of acceptance/rejection: January 25th, 2008 Deadline for submission of text: May, 2008 Information for Speakers: Regrettably, IFLA's Sections do not have funds available to pay for speakers’ expenses (e.g. registration fees, travel expenses, or accommodation costs). However, there may be limited funding available through other IFLA channels, especially for people from developing countries. For further information: Heather Todd Executive Manager, Engineering and Sciences Library Service University of Queensland Library, St Lucia Campus St Lucia QLD 4072 AUSTRALIA Phone: +61 7 334 64394 E-mail: h.todd@library.uq.edu.au
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 | 0.007 | 0.016 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.005 | 0.001 |
| Scholarly communication | 0.011 | 0.006 |
| Open science | 0.003 | 0.007 |
| Research integrity | 0.012 | 0.007 |
| Insufficient payload (model declined to judge) | 0.840 | 0.741 |
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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
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".