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Polychlorinated biphenyl (PCB) half-lives in humans: A systematic review

2023· review· en· W4387530098 on OpenAlexaff
Ifeoluwa Idowu, David Megson, Guuske P. Tiktak, Mike Dereviankin, Courtney D. Sandau

Bibliographic record

VenueChemosphere · 2023
Typereview
Languageen
FieldEnvironmental Science
TopicToxic Organic Pollutants Impact
Canadian institutionsMount Royal University
Fundersnot available
KeywordsPolychlorinated biphenylPopulationBreastfeedingEnvironmental healthMedicineDemographyGerontologyPediatricsEnvironmental chemistryChemistry

Abstract

fetched live from OpenAlex

This manuscript presents a systematic review of PCB half-lives reported in the scientific literature. The review was completed in accordance with PRISMA guidelines and included a review of almost 1000 peer-reviewed publications. In total, 26 articles were found to report half-lives in humans, with the majority of data coming from studies performed in North America on individuals suspected to have been exposed to PCBs. Terminology for reporting PCB half-lives was inconsistent, so we have attempted to consolidate this and recommend using either "apparent half-life" or "intrinsic half-life" in future studies. Within the literature, values for reported half-lives varied considerably for different PCBs. Less chlorinated PCBs generally have shorter half-lives than more chlorinated PCBs. It was interesting to note the large variability of half-lives reported for the same PCB. For example, the reported half-life for PCB 180 varied by nearly 3 orders of magnitude (0.34 years-300 years). Our review identified that the half-lives estimated were largely dependent on the studied cohort. We discuss the importance of PCB body burden, degree of chlorination and PCB structure, gender, age, breastfeeding, BMI, and smoking status on half-life estimations. We also identified significantly shorter half-lives for some PCBs in occupationally exposed individuals compared to results reported from the general population. PCB half-lives are not the same for every PCB or every individual. Therefore, careful consideration is needed when these values are used in human exposure studies.

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)0.002
metaresearch head score (Gemma)0.009
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: Systematic review
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.014
Threshold uncertainty score0.028

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.009
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0050.006
Bibliometrics0.0040.007
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.040
GPT teacher head0.312
Teacher spread0.272 · 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 designSystematic review
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
Published2023
Admission routes1
Has abstractno

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