Bibliographic record
Abstract
Registration is now open for the Spring 2008 online course EBM and the Medical Librarian. The course will run from January 14 – March 9, 2008. This course is an introduction to evidence-based medicine (EBM) for medical librarians and the role of the librarian to support its practice. Participants will learn to identify the parts of a well built clinical question, to recognize the validity criteria for research studies, and to identify roles that librarians can undertake in providing EBM training and support. The course utilizes course material, independent readings, reviews, and practice exercises. It is offered as an eight week distance education MLA CE course through the University of North Carolina's School of Information and Library Science. The distance education version of this course will be held January 14 to March 7, 2008. The course uses the Blackboard course management system. It is approved for 10 MLA CE units. The cost of the course is $400 (USD) and payment must be received with the registration form. There are only 4 seats left in the Spring class. Those unable to secure a seat can be added to the waitlist for the next session scheduled for Fall 2008. If you want to reserve your seat while processing payment, please email Stephanie Peterson at peterssb@email.unc.edu with your intentions. Additional course information and the registration form are available at: http://sils.unc.edu/programs/continuing_ed/ebm.html. If you have any questions about the course, please contact one of the course instructors: Connie Schardt (mschar005@mc.duke.edu) or Angela Myatt (myattae@ucmail.uc.edu).
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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 | 0.015 | 0.053 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.004 | 0.006 |
| Science and technology studies | 0.008 | 0.003 |
| Scholarly communication | 0.024 | 0.020 |
| Open science | 0.004 | 0.014 |
| Research integrity | 0.015 | 0.009 |
| Insufficient payload (model declined to judge) | 0.657 | 0.634 |
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".