Bibliographic record
Abstract
Scurvy, the condition associated with severe vitamin C deficiency, is believed to be one of the oldest diseases in human history. It was particularly prevalent during the Age of Sail, when long sea voyages without access to fresh food resulted in an epidemic which claimed millions of lives; however, scurvy has existed across time and geography, occurring whenever and wherever diets are devoid of vitamin C. Young children, specifically, were affected by the emergence of ‘infantile scurvy’ in the 19th century owing to the use of heated milk and manufactured infant foods of poor nutritional quality. Scurvy continues to occur in at-risk groups. In children and youths, it is primarily observed in the context of autism spectrum disorder and feeding problems such as a limited food repertoire and high-frequency single food intake. Diagnosis may be delayed and invasive testing undertaken owing to clinicians’ lack of familiarity with the disease, or the mistaken assumption that it is exclusively a disease of the past. The aetiology, clinical manifestations and treatment of scurvy are described. Its long history and current epidemiology are also reviewed, demonstrating that scurvy is very much a disease of the present. It is suggested that future efforts should focus on (i) anticipatory guidance and early nutritional intervention, informed by an understanding of scurvy’s epidemiology, with the aim of preventing the disease in those at risk, and (ii) prompt recognition and treatment to minimise morbidity and healthcare costs.Abbreviations: ASD: autism spectrum disorder.
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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.003 | 0.006 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.005 | 0.008 |
| Insufficient payload (model declined to judge) | 0.005 | 0.002 |
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".