Unheard, unseen and unprotected: DOHaD council’s call for action to protect the younger generation from the long-term effects of COVID-19
Bibliographic record
Abstract
Globally, we are living through one of the most serious public health crises in recent history. Apart from the obvious health risks, the COVID-19 pandemic is exposing the damaging impact of inequalities. The risk of contracting SARS-CoV-2 infection and of hospitalization and mortality rates differ greatly among different communities and populations. In high income countries, Black, Indigenous and People of Colour, low socioeconomic position communities and those living in high density population areas appear to be more at risk. In addition, pre-existing conditions such as obesity, type 2 diabetes or hypertension are contributing factors to greater morbidity and mortality for those infected with SARS-CoV-2. Similar sequelae of these pre-existing conditions are emerging in low and middle-income countries, although as yet the data are limited. There is also disparity in gender related risk, with men facing greater morbidity and mortality due to COVID-19 than women. It has emerged, however, that women will face greater social and economic consequences of this pandemic. This gender-based discrepancy, combined with little evidence for maternal-fetal transmission of the coronavirus and the disease burden among children also being low, may focus health action more on older men than on mothers and children. This concern is a predominant reason for this position paper on behalf of the board of the International DOHaD Society
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 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".