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Record W2147868914 · doi:10.1017/s0965539510000057

EPIGENETIC PROGRAMMING AND FETAL GROWTH RESTRICTIONS

2010· article· en· W2147868914 on OpenAlexaff
José Carlos Ferreira, Sanaa Choufani, John‏ Kingdom, Rosanna Weksberg

Bibliographic record

VenueFetal and Maternal Medicine Review · 2010
Typearticle
Languageen
FieldMedicine
TopicBirth, Development, and Health
Canadian institutionsMount Sinai HospitalHospital for Sick ChildrenUniversity of Toronto
Fundersnot available
KeywordsFetal growthMedicineFetal programmingFetusEpigeneticsDiseaseIntrauterine growth restrictionInsulin resistanceDiabetes mellitusBioinformaticsPregnancyEndocrinologyInternal medicineBiologyGenetics

Abstract

fetched live from OpenAlex

Normal fetal growth and development depends on multiple molecular mechanisms that coordinate both placental and fetal development. Efforts to better understand fetal/placental growth dysregulation and fetal growth restriction (FGR) are now being driven by several findings that highlight the longterm impact of FGR on susceptibility to disease. The association of poor fetal growth to perinatal medical complications is well accepted but more recent data also show that FGR is linked to common, serious adult health problems. Several large-scale human epidemiological studies from diverse countries have shown that conditions such as coronary heart disease, hypertension, stroke, type 2 diabetes mellitus, adiposity, insulin resistance and osteoporosis are more prevalent in individuals with a history of low birthweight.

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)0.000
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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.720
Threshold uncertainty score0.414

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.025
GPT teacher head0.312
Teacher spread0.288 · 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 designObservational
Domainnot available
GenreEmpirical

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

Citations2
Published2010
Admission routes1
Has abstractyes

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