Bibliographic record
Abstract
As veterinarians gather in Halifax for the CVMA's annual convention, another presidential term comes to an end. My fifteen minutes went by so fast.... Since last year's get- together in Vancouver, many dedicated volunteers and staff have contributed to the continued success of the CVMA as a national association. To list all the accomplishments over the last year would take up more space than I've been allocated, so I'll just touch on some of the highlights. The new National Benchmarking program, in development and set to be launched in July 2002, will enhance the CVMA's “Successful Practice of Veterinary Medicine” priority by providing participating members valuable insight into their financial future. This important initiative will be the foundation from which the profession's economic health will rise. The CVMA's appearance before the Parliamentary Standing Committe on Justice and Human Rights to present a brief on Bill C-15 demonstrated the profession's commitment to the humane treatment and welfare of animals. The CVMA's increased activities in the public policy advocacy arena have raised the association's political profile. Working with the deans, the CVMA's Senior Advisor brought the very important issue of federal investment in the 4 Canadian Veterinary Colleges to the minds of opinion leaders and decision makers. Moreover, in concert with other interested groups, the CVMA made effective representation to the Veterinary Drugs Directorate of Health Canada to adopt a system for expedited review of veterinary drug submissions. There are many people to thank in this, my last message. I had the pleasure of working with 2 wonderful Executive Directors, Claude Paul Boivin and Jost am Rhyn. The staff in Ottawa as well as the CVMA committee volunteers deserve a lot of praise. The CVMA Council has been very supportive and dynamic. My business partners in Antigonish were forgiving and patient. And mostly, my wife, Anita, and my children deserve a great deal of gratitude for their support and understanding. I enjoyed meeting many of you, the members, over the last few years. I hope you stay committed to the vision of a national association whose number one priority is improving the lives of its members, those of their loved ones, and the lives of those who depend on veterinarians for their well-being. Lastly, I'm looking forward to the coming year and Jeanne Lofstedt's term as President. Jeanne brings to the presidency an understanding of veterinary students and new graduates that will help the CVMA grow and adapt to the new realities of the profession. I wish her and Council the very best, and I wish all of you, health, happiness and time to spend with your families.
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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 | 0.005 | 0.015 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.009 | 0.003 |
| Scholarly communication | 0.018 | 0.006 |
| Open science | 0.002 | 0.014 |
| Research integrity | 0.004 | 0.012 |
| Insufficient payload (model declined to judge) | 0.189 | 0.167 |
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".