Ancestral childhood environmental exposures occurring to the grandparents and great-grandparents of the ALSPAC study children
Bibliographic record
Abstract
Background: Cohort studies tend to be designed to look forward from the time of enrolment of the participants, but there is considerable evidence that the previous generations have a particular relevance not only in the genes that they have passed on, their cultural beliefs and attitudes, but also in the ways in which previous environmental exposures may have had non-genetic impacts, particularly for exposures during fetal life or in childhood. Methods: To investigate such non-genetic inheritance, we have collected information on the childhoods of the ancestors of the cohort of births comprising the original Avon Longitudinal Study of Parents and Children (ALSPAC). The data collected on the study child’s grandparents and great grandparents comprise: (a) countries of birth; (b) years of birth; (c) age at onset of smoking; (d) whether the ancestral mothers smoked during pregnancy; (e) social class of the household; (f) information on 19 potentially traumatic situations in their childhoods such as death of a parent, being taken into care, not having enough to eat, or being in a war situation; (g) causes of death for those ancestors who had died. The ages at which the individual experienced the traumatic situations distinguished between ages <6; 6–11, and 12–16 years. The numbers of ancestors on which data were obtained varied from 1128 paternal great-grandfathers to 4122 maternal great grandmothers. These ancestral data will be available for analysis to bona fide researchers on application to the ALSPAC Executive Committee.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".