Thirty years of the "Anica Bitenc Travelling Fellowship" - a tribute to Dr. Igor A.S. Bitenc.
Bibliographic record
Abstract
Thirty years ago, in 1984, Dr. Igor A. S. Bitenc, M.D., F.R.C.S.(C), a retired orthopaedic surgeon from Canada, who was of Yugoslav descent, and who had always remained attached to his original homeland, founded a travelling fellowship for young orthopaedic surgeons from former Yugoslavia named the "Anica Bitenc Travelling Fellowship" after his late mother. The first Fellow visited Canada in 1985 and was followed by five Fellows from different areas of Yugoslavia in successive years. Due to the tragic war in Yugoslavia in the 90's, the Fellowship was postponed for several years. It was resumed in 1997, but only for three newly formed states of Croatia, Slovenia and Serbia. Funding of the Fellowship was provided by an endowment from Dr. Bitenc and managed by the Canadian Orthopaedic Association, which hosts one Fellow per year on the rotational basis from Slovenia, Croatia and Serbia. The Fellowship finally proved to be very successful and, owing to the benevolence of Dr. Bitenc, 24 young orthopaedic surgeons from various regions of former Yugoslavia have had the opportunity to visit the best orthopaedic centres in Canada so far. Dr. Bitenc has ensured the Fellowship will continue for many years to come by bequeathing an endowment of $ 300.000. This unforgettable act of human nobility and patriotic sensibility will be of enormous help in future to many orthopaedic surgeons and their numerous patients in the countries of South Slavs.
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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 | 0.007 | 0.023 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.002 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.006 | 0.015 |
| Insufficient payload (model declined to judge) | 0.022 | 0.014 |
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".