Bibliographic record
Abstract
Dear Friends and Colleagues,It has been quite the eventful past year already, and I wanted to provide an updateas we move through into the latter half of 2025 and prepare for some excitingevents into 2026. This year, we have had multiple wins, starting with the launchof the Canadian Journal of Wound, Ostomy and Continence this past April. We thenmoved into our highly successful conference held in May, and we now anticipate the World Council of Enterostomal Therapy Congress, which will be conducted jointly with Nurses Specialized in Wound, Ostomy and Continence Canada in April 2026.I look forward to the opportunity to see many of you in person at this event.We have focused this past year on recognizing our members. Launching the Fellowship in Nursing Specialized in Wound, Ostomy and Continence (FNSWOC) is but one example of this. I would also be remiss if I didn’t recognize and mention the retirement announcement of our very own Chief Executive Officer, Catherine Harley. Cathy has been with us for over 20 years and has moved our association from a small grassroots organization to an association impacting the lives of those living with wound, ostomyand continence needs across Canada and on a global scale. As we move forward into the latter half of 2025, I want to recognize and thank Cathy for all the hard work thesepast years and all the lives she has managed to touch. Thank you, Cathy.The NSWOCC board has now obtained an executive search firm who we willwork with to seek out our next CEO. The upcoming months will be quite exciting as we move to secure the future of our association through team expansion and seeking out continued opportunities and ways in which our association can continue to grow and impact the health care of those with wound, ostomy and continence issues. As part of this future, we recognize the rapidly evolving health care landscape, particularly the opportunities presented by advancements such as artificial intelligence. Innovation will remain central to our mission, ensuring that we continue to adapt, grow, and provide leadership in our tri-specialty.
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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 | 0.003 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.014 | 0.015 |
| Insufficient payload (model declined to judge) | 0.082 | 0.038 |
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".