Evidence map›Paper›PMID 39670560›Full record

ArticleEnvironmental science & technology2025

Challenges in Observation of Ultrafine Particles: Addressing Estimation Miscalculations and the Necessity of Temporal Trends.

Tzu-Chi Lin, Pei-Te Chiueh, Ta-Chih Hsiao

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Environmental science & technology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. Air pollution and alveolar health.European respiratory review : an official journal of the European Respiratory Society · 2025
    Review
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

3 authors.

Tzu-Chi LinGraduate Institute of Environmental Engineering, College of Engineering, National Taiwan University, 71 Chou-Shan Road, Taipei 106, Taiwan.ORCID 0000-0001-7168-0718
Pei-Te ChiuehGraduate Institute of Environmental Engineering, College of Engineering, National Taiwan University, 71 Chou-Shan Road, Taipei 106, Taiwan.ORCID 0000-0002-3395-4164
Ta-Chih HsiaoGraduate Institute of Environmental Engineering, College of Engineering, National Taiwan University, 71 Chou-Shan Road, Taipei 106, Taiwan.ORCID 0000-0003-4103-6272

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Ultrafine particles (UFPs) pose a significant health risk, making comprehensive assessment essential. The influence of emission sources on particle concentrations is not only constrained by meteorological conditions but often intertwined with them, making it challenging to separate these effects. This study utilized valuable long-term particle number and size distribution (PNSD) data from 2018 to 2023 to develop a tree-based machine learning model enhanced with an interpretable component, incorporating temporal markers to characterize background or time series residuals. Our results demonstrated that, differing from PM

Indexed as

Air PollutantsEnvironmental MonitoringParticulate MatterParticle SizeAir PollutantsParticulate Matteranthropogenic fluctuationdeweather methodparticle number size distributionsSHAP-based model interpretationtime series residualsUFPs

Identifiers

PMID39670560
PMCPMC11741106

What OpenQuestion holds

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LicenceCC BY
Read underepoch 390

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 OpenQuestion graph.