2018 CVM News: Medicine without borders: Cornell cardiologists travel the world to improve treatment at home and abroad
Bibliographic record
Abstract
This news item is about: During years of working together to treat conditions from heart failure to congenital heart defects and arrhythmias, a team of cardiologists at Cornell has been perfecting the art of collaboration on campus. Now they're forming meaningful relationships around the globe — to save lives near and far. Board-certified veterinary cardiologists Dr. N. Sydney Moïse, M.S. '85; associate professor Dr. Romain Pariaut; senior extension associate Bruce Kornreich, D.V.M. '92, Ph.D. '05 and adjunct professor Dr. Roberto Santilli, head of cardiology at the Clinica Veterinaria Malpensa in Italy, have brought their expertise to countries such as Russia, China, Portugal, India, Spain, Germany, France, Great Britain, Italy, Brazil, Taiwan and others in the form of workshops and conferences on arrhythmia for veterinarians at all stages of their careers.
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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 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.009 | 0.009 |
| Insufficient payload (model declined to judge) | 0.184 | 0.084 |
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".