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Record W2150199104 · doi:10.1098/rspb.2010.2627

The evolutionary biology of child health

2011· review· en· W2150199104 on OpenAlexaff
Bernard J. Crespi

Bibliographic record

VenueProceedings of the Royal Society B Biological Sciences · 2011
Typereview
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicGenetic Syndromes and Imprinting
Canadian institutionsSimon Fraser University
Fundersnot available
KeywordsBiologyEpigeneticsContext (archaeology)Genomic imprintingOffspringEvolutionary developmental biologyDiseaseLineage (genetic)Human evolutionDevelopmental psychologyEvolutionary biologyGeneticsGenePsychologyMedicinePregnancyDNA methylation

Abstract

fetched live from OpenAlex

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.

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 distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.986
Threshold uncertainty score0.703

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.000
Science and technology studies0.0010.002
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.044
GPT teacher head0.305
Teacher spread0.261 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreReview

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".

Quick stats

Citations38
Published2011
Admission routes1
Has abstractyes

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