Bibliographic record
Abstract
I apply evolutionary perspectives and conceptual tools to analyse central issues underlying child health, with emphases on the roles of human-specific adaptations and genomic conflicts in physical growth and development. Evidence from comparative primatology, anthropology, physiology and human disorders indicates that child health risks have evolved in the context of evolutionary changes, along the human lineage, affecting the timing, growth-differentiation phenotypes and adaptive significance of prenatal stages, infancy, childhood, juvenility and adolescence. The most striking evolutionary changes in humans are earlier weaning and prolonged subsequent pre-adult stages, which have structured and potentiated maladaptations related to growth and development. Data from human genetic and epigenetic studies, and mouse models, indicate that growth, development and behaviour during pre-adult stages are mediated to a notable degree by effects from genomic conflicts and imprinted genes. The incidence of cancer, the primary cause of non-infectious childhood mortality, mirrors child growth rates from birth to adolescence, with paediatric cancer development impacted by imprinted genes that control aspects of growth. Understanding the adaptive significance of child growth and development phenotypes, in the context of human-evolutionary changes and genomic conflicts, provides novel insights into the causes of disease in childhood.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.001 | 0.005 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".