Bibliographic record
Abstract
International Interprofessional Wound Care Course After nearly 15 years of conducting the International Interprofessional Wound Care Course (IIWCC) in Canada, West Asia, and Africa, the IIWCC is coming to the United States. The first class will be held August 8–11, 2013, at New York University (NYU) Medical Center, in New York, New York. R. Gary Sibbald, BSc, MD, MEd, FRCPC (Med Derm), MACP, FAAD, MAPWCA, and Diane L. Krasner, PhD, RN, created the interprofessional yearlong course about the essentials of wound care. In Canada, the IIWCC is considered a “credential” for wound care. More than 1000 practitioners worldwide have graduated from the IIWCC. And, IIWCC graduates have been involved in bringing the “60-Second High Risk Diabetic Foot Screening Tool” and interprofessional coordinated care to Guyana, South America, where diabetic foot amputations have been reduced by 68%. A similar framework for improved patient outcomes has been introduced to Africa and West Asia. The IIWCC-NYU is cosponsored by the Department of Nursing, NYU Langone Medical Center, and course director is Elizabeth A. Ayello, PhD, RN, ACNS-BC, CWON, ETN, MAPWCA, FAAN. It is accredited though the Office of Continuing Education and Professional Development, Faculty of Medicine, University of Toronto. Credits from the course are eligible for advanced standing if a graduate is accepted into the Master of Science, Community Health program (prevention and wound care), School of Graduate Studies University of Toronto, or for the master’s program at Stellenbosch University in Cape Town, South Africa. The IIWCC is designed for those with some education and wound care experience, including physicians, nurses, and allied health professionals in the wound care field and related industries. Course participants will assess and critically review wound care and education literature in key subject areas (residential weekends, modules), integrate wound care and education principles by a self-directed modular learning program, and demonstrate the application of best practices by small interprofessional patient management teams and developing a selective related to the learner’s everyday activities. Register early online at http://www.WoundPedia.com. For more information, e-mail [email protected] or call 905-272-9009. ▴Information:http://www.WoundPedia.com
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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 | 0.001 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.851 | 0.610 |
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".