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Record W2148506810 · doi:10.2217/epi.12.58

Epigenetics of Early-Life Lead Exposure and Effects on Brain Development

2012· review· en· W2148506810 on OpenAlexaff
Marie-Claude Senut, Pablo Cingolani, Arko Sen, Adéle Kruger, Asra N. Shaik, Helmut V. B. Hirsch, Steven T. Suhr, Douglas M. Ruden

Bibliographic record

VenueEpigenomics · 2012
Typereview
Languageen
FieldEnvironmental Science
TopicHeavy Metal Exposure and Toxicity
Canadian institutionsMcGill UniversityMcGill University and Génome Québec Innovation Centre
FundersNational Institute of Environmental Health Sciences
KeywordsEpigeneticsBiologyEpigenesisNeuroscienceDNA methylationBioinformaticsGeneticsGeneGene expression

Abstract

fetched live from OpenAlex

The epigenetic machinery plays a pivotal role in the control of many of the body's key cellular functions. It modulates an array of pliable mechanisms that are readily and durably modified by intracellular or extracellular factors. In the fast-moving field of neuroepigenetics, it is emerging that faulty epigenetic gene regulation can have dramatic consequences on the developing CNS that can last a lifetime and perhaps even affect future generations. Mounting evidence suggests that environmental factors can impact the developing brain through these epigenetic mechanisms and this report reviews and examines the epigenetic effects of one of the most common neurotoxic pollutants of our environment, which is believed to have no safe level of exposure during human development: lead.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.002
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.001

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.

Opus teacher head0.042
GPT teacher head0.279
Teacher spread0.236 · 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 source (direct Gemma or distilled Codex), 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

Citations145
Published2012
Admission routes1
Has abstractyes

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