MEMORIUM A Road to Learning With a Character as Noble as an Orchid and a Career as Steady as a Pine Tree
Bibliographic record
Abstract
Dr Zhu Shoumin was a steadfast friend who believed in the warmth of friendship. Zhu gave his all to those that knew him. He was a shining light that guided us with his happy enthusiasm, visionary NUTRIOLOGICAL thinking and his exemplary work ethos and energy. In the last 30 years, he coauthored important classic article that have been published in the international journals and he made contributions to presentations in India, UK, Canada. We will always think of him as a great friend and his parting is a great loss. We in the International College of Nutrition knew him for the last 30 years, planned great adventures with him in India and China as well as in Canada on Cardiovascular Diseases and somehow these should be kept alive. He organised the 5th World Congress on Clinical Nutrition at Zhejiang Medical University, Hangzhou, China in 1995 which is unforgettable.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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 teacher head, 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".