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The Impact of Toxins on the Developing Brain

2015· review· en· W2118690430 on OpenAlexaff
Bruce P. Lanphear

Bibliographic record

VenueAnnual Review of Public Health · 2015
Typereview
Languageen
FieldEnvironmental Science
TopicHeavy Metal Exposure and Toxicity
Canadian institutionsBC Children's HospitalChild and Family Research InstituteSimon Fraser UniversityUniversity of British Columbia
Fundersnot available
KeywordsBrain developmentVulnerability (computing)Brain functionPublic healthPopulationEnvironmental healthMedicineBiologyNeuroscienceComputer securityPathologyComputer science

Abstract

fetched live from OpenAlex

The impact of toxins on the developing brain is usually subtle for an individual child, but the damage can be substantial at the population level. Numerous challenges must be addressed to definitively test the impact of toxins on brain development in children: We must quantify exposure using a biologic marker or pollutant; account for an ever-expanding set of potential confounders; identify critical windows of vulnerability; and repeatedly examine the association of biologic markers of toxins with intellectual abilities, behaviors, and brain function in distinct cohorts. Despite these challenges, numerous toxins have been implicated in the development of intellectual deficits and mental disorders in children. Yet, too little has been done to protect children from these ubiquitous but insidious toxins. The objective of this review is to provide an overview on the population impact of toxins on the developing brain and describe implications for public health.

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)0.001
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 score0.003
Threshold uncertainty score0.011

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.001
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.001

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 head0.158
GPT teacher head0.442
Teacher spread0.283 · 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

Citations187
Published2015
Admission routes1
Has abstractyes

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