Information Resources Group (IRG) Workshop: Pushing the Frontiers of HTA Information Management
Bibliographic record
Abstract
Make the IRG pre-conference workshop part of your annual HTAi (Health Technology Assessment International) meeting plans! Join us in Barcelona on Sunday, June 17th for a full day of training and lively discussions. Our workshop includes a mixture of presentations and interactive sessions highlighting important and emerging developments in HTA information management. Julie Glanville, IS Manager and Associate Director at the Centre for Reviews and Dissemination in York, will outline recent research into search filters to identify diagnostic tests and assessments of which databases and other resources should be searched for diagnostic test studies. Greg Bak, an information specialist from the Canadian Agency for Drugs and Technologies in Health, will discuss a CADTH-adapted critical appraisal instrument that can be used to rank and assess the quality of methodological search filters. His presentation will provide participants with the skills needed to make informed decisions about when and which methodological search filters to use. Sari Ormstad, a research librarian at the Norwegian Knowledge Centre for the Health Services, Oslo, will present on a new database that offers local decision-makers and health personnel an overview of all current international assessments of new health technologies and summarises those that are most relevant for them. Miquel Mayer, Director of Web Mèdica Acreditada, an international accreditation program of medical websites, will discuss the quality and use of health-related websites, different strategies to select and improve their quality, and finally how metadata and semantic web technologies could help users find the best health information. Elaine Alligood, an information specialist from Veterans Affairs Technology Assessment Program, will update participants on current search engines and how they can be used in HTA searches to complement traditional database searching. Andrew Booth, Director of Information Resources at the School of Health & Related Research (ScHARR), and Amanda Burls, Senior Clinical Lecturer and Director of West Midlands Health Technology Assessment Collaboration, will deliver a half-day bilingual (English and Spanish) critical appraisal workshop in which they provide a "tapas" of critical appraisal skills and techniques. The workshop will demonstrate that skills in critical appraisal can be modeled and facilitated by library, information and other health staff working locally. Full details regarding conference registration are available at: http://www.htai.org/barcelona-2007/. For more information, contact Becky Skidmore, IRG Chair: bskidmore@sogc.com or Malene Fabricius Jensen, IRG Chair-Elect: mfj@sst.dk.
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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 | 0.287 | 0.312 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.003 | 0.004 |
| Bibliometrics | 0.008 | 0.009 |
| Science and technology studies | 0.007 | 0.009 |
| Scholarly communication | 0.034 | 0.028 |
| Open science | 0.009 | 0.020 |
| Research integrity | 0.019 | 0.032 |
| Insufficient payload (model declined to judge) | 0.081 | 0.053 |
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".