Introduction of oral vitamin D supplementation and the rise of the allergy pandemic
Bibliographic record
Abstract
The history of the allergy pandemic is well documented, enabling us to put the vitamin D hypothesis into its historical context. The purpose of this study is to compare the prevalence of rickets, vitamin D supply, and allergy prevalence at 50-year intervals by means of a retrospective analysis of the literature since 1880. English cities in 1880 were characterized by an extremely high rickets prevalence, the beginning of commercial cod liver oil production, and the near absence of any allergic diseases. By 1930 hay fever prevalence had risen to about 3% in English-speaking countries where cod liver oil was preferentially used for the treatment of rickets. In 1980 vitamin D was used nation-wide in all industrialized countries as supplement to industrial baby food, thus eradicating nearly all cases of rickets. At the same time the allergy prevalence reached an all-time high, affecting about 30% of the population. Time trends are therefore compatible with the vitamin D hypothesis although direct conclusions cannot be drawn. It is interesting, however, to note that there are at least two earlier research papers linking synthesized vitamin D intake and allergy (Reed 1930 and Selye 1962) published prior to the modern vitamin D hypothesis first proposed in 1999.
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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".