A Probabilistic Framework for Multimedia Dioxin Risk Assessment in Susceptible Populations.

Kuan-Yi Chen, Chien-Cheng Jung, Ken-Hui Chang, Chow-Feng Chiang

Abstract read

In one paragraph

Article in Toxics, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it

0cells of the map it votes in

0citing papers in PubMed

–field-weighted citation impact

1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

Kuan-Yi ChenDepartment of Public Health, China Medical University, Taichung 406040, Taiwan.

Chien-Cheng JungDepartment of Public Health, China Medical University, Taichung 406040, Taiwan.

Ken-Hui ChangDepartment of Safety Health and Environmental Engineering, National Yunlin University of Science and Technology, Yunlin 640301, Taiwan.

Chow-Feng ChiangDepartment of Public Health, China Medical University, Taichung 406040, Taiwan.ORCID 0000-0003-4035-6020

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

In this study, a probabilistic framework was developed to address uncertainty in multimedia risk assessment for susceptible populations while capturing population variability, illustrated by dioxin emissions from municipal solid waste incinerators. The framework integrates emission estimation, AERMOD dispersion modeling, and MEPAS multimedia modeling. Cancer risks were evaluated with dose-based slope factors and age-dependent adjustment factors (ADAFs) for early-life susceptibility. Three assessment approaches were compared: deterministic without ADAF adjustment, deterministic with ADAF adjustment, and probabilistic with ADAF adjustment. For the general population (

Indexed as

AERMODage-dependent adjustment factorsMEPASMonte Carlo simulationmunicipal solid waste incineration

Identifiers

PMID42515136

DOI10.3390/toxics14070571

PMCPMC13416591

What Socratic holds

Textmetadata

LicenceCC BY

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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.