Bibliographic record
Abstract
Dear Colleagues, I am pleased to welcome you to the inaugural issue of the Canadian Journal of Wound, Ostomy and Continence (CJWOC). CJWOC is an open-access, peer-reviewed journal with no article processing fees for authors, offering a platform for Canadian clinicians to share innovative practices in wound, ostomy, and continence. I encourage you to explore this publication and consider how the innovative and creative ways in which you practice could make for an informative and educational article. While our association continues to expand on our academic offerings through our new publication, we are also preparing for our upcoming annual national conference in Montreal where you can network and benefit from excellent educational topics. We will continue with many important projects occurring throughout Canada including multiple best practice documents. Our educational offerings continue to expand through the recently announced partnership to provide the Indigenous ECHO Canada Skin and Wound program. The Ontario Ministry of Long-Term Care also recently announced their investment in funding the education of 90 new Skin Wellness Associate Nurses (SWANs) within the Long-Term Care setting. This expansion of access to wound, ostomy and continence education is set to have a significant impact on the care of patients in these frequently underrepresented settings. As we move into 2025, we continue to prioritize the recognition and contributions of our members, and I am proud to announce our upcoming Fellowship program, recognizing those who have made significant contributions to our specialty. Further details will be shared in the coming months. I look forward to an eventful 2025 as we continue to grow and improve upon care for patients with wound, ostomy, and continence needs and advocate for those who care for them.
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 | 0.004 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.008 | 0.002 |
| Scholarly communication | 0.006 | 0.004 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.011 | 0.023 |
| Insufficient payload (model declined to judge) | 0.036 | 0.011 |
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".