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Record W2599844136 · doi:10.2147/dmso.s95296

Early-life chemical exposures and risk of metabolic syndrome

2017· review· en· W2599844136 on OpenAlexaff
Nicole E. De Long, Alison C. Holloway

Bibliographic record

VenueDiabetes Metabolic Syndrome and Obesity · 2017
Typereview
Languageen
FieldMedicine
TopicBirth, Development, and Health
Canadian institutionsMcMaster University
Fundersnot available
KeywordsMetabolic syndromeEnvironmental healthMedicineInternal medicineObesity

Abstract

fetched live from OpenAlex

The global prevalence of obesity has been increasing at a staggering pace, with few indications of any decline, and is now one of the major public health challenges worldwide. While obesity and metabolic syndrome (MetS) have historically thought to be largely driven by increased caloric intake and lack of exercise, this is insufficient to account for the observed changes in disease trends. There is now increasing evidence to suggest that exposure to synthetic chemicals in our environment may also play a key role in the etiology and pathophysiology of metabolic diseases. Importantly, exposures occurring in early life (in utero and early childhood) may have a more profound effect on life-long risk of obesity and MetS. This narrative review explores the evidence linking early-life exposure to a suite of chemicals that are common contaminants associated with food production (pesticides; imidacloprid, chlorpyrifos, and glyphosate) and processing (acrylamide), in addition to chemicals ubiquitously found in our household goods (brominated flame retardants) and drinking water (heavy metals) and changes in key pathways important for the development of MetS and obesity.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.485
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0080.001
Bibliometrics0.0010.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.001
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 head0.043
GPT teacher head0.312
Teacher spread0.269 · 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.

Study designObservational
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

Citations81
Published2017
Admission routes1
Has abstractyes

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