Aetiology of Oesophageal Cancer in Africa - A Review of Historical and Current Evidence
Bibliographic record
Abstract
There is no current agreement on the cause of squamous cancer of the oesophagus in Africa, a major cause of morbidity and mortality in East and Southern Africa. The remarkable history is reviewed together with all recent evidence using a literature search. There are consistent and continuing associations with maize and with tobacco. Changes of type of maize, patterns of consumption and processing occurred around 1930, and a rapid rise of oesophageal cancer dated from that time. Tobacco has a worldwide association with cancer of the oesophagus, but there is a substantial minority of non-users in high incidence areas. Other carcinogens have come under suspicion, but there is evidence against any of these acting as the principal carcinogenic influence in Africa. Recent studies in Japan and in South Africa have shown an association between non-acid gastro-oesophageal reflux and squamous cancer of the oesophagus. There is no credible candidate for principal oesophageal carcinogen in Africa. There is good reason to look again at milled maize: its deficiencies, contaminations, and degenerative processes. Associations between diet, non-acid reflux and squamous cancer of the oesophagus merit further study.
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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.004 | 0.006 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".