Bibliographic record
Abstract
Diversity, many languages, a rainbow of faces, and a harmonious ethnic mix… these are what make Winnipeg unique! We invite you to join us on this special anniversary. Come for the great continuing education sessions, networking opportunities, exhibit hall, the golf tournament, a Folklorama Family Night, and tours for adult companions, teens and pre-teens. From the Meet & Greet through the Current Issues Update Forum and Awards Presentation Luncheon, you will be sure to find the experience a rewarding one. Detailed information on topics and speakers, with a special session on a potpourri of emerging diseases (such as West Nile virus) is in your Preliminary Brochure, sent to you with this issue. The brochure is also on our Web site at www.canadianveterinarians.net under programs. A full Program and Registration Guide will be available in March. Set aside the dates today. Plan to bring the whole family! For further information please contact the CVMA at 1-800-567-2862 ext. 23 or (613) 236-1162 ext. 23; fax: (613) 236-9681; e-mail: gro.vmca-amvc@titeptnomm (by Angie Herzog, Manager, Professional Development)
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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.007 | 0.001 |
| Scholarly communication | 0.004 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.518 | 0.193 |
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".