Bibliographic record
Abstract
When first described in 1958, Burkitt lymphoma was considered by many to be an African curiosity. However, over the next few decades, over 10,000 publications on Burkitt lymphoma would influence many facets of oncology research including immunology, molecular genetics, chemotherapy, and viral oncology. At the time of discovery, its distribution in equatorial Africa was unique; it was where a child was born and lived, and not what race they were, that conveyed the greatest incidence risk. Its association with Epstein-Barr virus brought attention to the possibility that oncogenesis may be influenced by viruses. The influence that Burkitt lymphoma had on furthering oncology is far-reaching, and it is fitting that the physician credited with bringing attention to this disease was himself broad in his influence. Denis Burkitt was a humanitarian surgeon whose work was not limited to Burkitt lymphoma: he instigated a plan to rid an entire Ugandan district of yaws, he designed and created affordable orthopaedic equipment that could be locally produced in Kampala, and he was an early advocate of a high fiber diet. The following article will examine the biography of Denis Burkitt, with a focus on how he was able to further oncology and global health.
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) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 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".