RE: “INVITED COMMENTARY: THE DISILLUSIONMENT OF DEVELOPMENTAL ORIGINS OF HEALTH AND DISEASE (DOHAD) EPIDEMIOLOGY”
Bibliographic record
Abstract
We were surprised by the first article in the January issue of the American Journal of Epidemiology. With the title “Invited Commentary: The Disillusionment of Developmental Origins of Health and Disease (DOHaD) Epidemiology” (1), we anticipated a broad discussion of epidemiology in DOHaD and a critique of the concept. Instead, we read a commentary on a 2018 paper by Masarwa et al. (2). The commentary notes that this systematic review was not very informative. We do not understand how criticism of an article on a specific topic could justify a title indicative of disillusionment with the epidemiology of DOHaD in its entirety, especially as the DOHaD concept focuses on developmental exposures other than teratology (3). The authors of the commentary themselves note that their criticism of the DOHaD concept is confined to medication use during pregnancy, but their concluding paragraph, which is dismissive of DOHaD, bears no relevance to their opinion of the article. The commentary’s title, while possibly reflecting the opinion of the authors, misrepresents the contents of the commentary, and we ask that it be amended and an erratum published. H.I., K.G., C.C., J.B., and M.B. are supported wholly or in part by the Medical Research Council. K.G. is also supported by the National Institute for Health Research (NIHR Senior Investigator Award NF-SI-0515-10042) and the British Heart Foundation (grant RG/15/17/3174). M.H. is supported by the British Heart Foundation. D.S. is supported by the Canada Research Chairs Program. L.P. is supported by King’s College London and Tommy’s Charity. All of the authors are members of the International Society for Developmental Origins of Health and Disease. K.G. is the Treasurer, C.C. was a founding Trustee and is a previous member of the DOHaD Council, M.H. is a past President, C.F. is a past Secretary and a Trustee, M.B. is a Trustee, D.S. is the current Secretary, and L.P. is the current President.
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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 | 0.017 | 0.101 |
| Meta-epidemiology (narrow) | 0.002 | 0.003 |
| Meta-epidemiology (broad) | 0.004 | 0.003 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.013 | 0.007 |
| Scholarly communication | 0.010 | 0.011 |
| Open science | 0.007 | 0.006 |
| Research integrity | 0.140 | 0.124 |
| Insufficient payload (model declined to judge) | 0.014 | 0.013 |
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".