Evidence map›Paper›PMID 32721685›Full record

ArticleChemosphere2020

Heavy metals in submicronic particulate matter (PM

Huiming Li, Qian'ying Dai, Meng Yang, Fengying Li, Xuemei Liu, Mengfan Zhou, Xin Qian

Open access · greenAbstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Chemosphere, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
1.9field-weighted citation impact, top 16% of its field
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

4 citing papers in PubMed, 33 citations in OpenAlex.

  1. A hybrid prediction model for PMScientific reports · 2026
    Article
  2. Article
  3. Article
  4. Bioaccessibility of potentially toxic elements in mine residue particles.Environmental science. Processes & impacts · 2021
    Article
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

7 authors at 4 institutions in 1 country.

Huiming LiSchool of Environment, Nanjing Normal University, Nanjing, 210023, China.
Qian'ying DaiState Key Laboratory of Pollution Control and Resources Reuse, School of the Environment, Nanjing University, Nanjing, 210023, China.
Meng YangJiangsu Collaborative Innovation Center of Atmospheric Environment and Equipment Technology (CICAEET), Nanjing University of Information Science & Technology, Nanjing, 210044, China; Jiangsu Key Laboratory of Atmospheric Environment Monitoring and Pollution Control, School of Environmental Science and Engineering, Nanjing University of Information Science & Technology, Nanjing, 210044, China.
Fengying LiJiangsu Collaborative Innovation Center of Atmospheric Environment and Equipment Technology (CICAEET), Nanjing University of Information Science & Technology, Nanjing, 210044, China; Jiangsu Key Laboratory of Atmospheric Environment Monitoring and Pollution Control, School of Environmental Science and Engineering, Nanjing University of Information Science & Technology, Nanjing, 210044, China.
Xuemei LiuState Key Laboratory of Pollution Control and Resources Reuse, School of the Environment, Nanjing University, Nanjing, 210023, China.
Mengfan ZhouState Key Laboratory of Pollution Control and Resources Reuse, School of the Environment, Nanjing University, Nanjing, 210023, China.
Xin QianState Key Laboratory of Pollution Control and Resources Reuse, School of the Environment, Nanjing University, Nanjing, 210023, China; Jiangsu Collaborative Innovation Center of Atmospheric Environment and Equipment Technology (CICAEET), Nanjing University of Information Science & Technology, Nanjing, 210044, China. Electronic address: xqian@nju.edu.cn.
Nanjing University of Information Science and Technology · CNNanjing University · CNNanjing Normal University · CNState Key Laboratory of Pollution Control and Resource Reuse · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The aim of this study was to establish a method for predicting heavy metal concentrations in PM

Indexed as

Neural Networks, ComputerAerosolsAir PollutantsAir PollutionBetacoronavirusChinaCitiesComputer SimulationCoronavirus InfectionsCOVID-19Environmental ExposureEnvironmental MonitoringHumansMetals, HeavyMeteorological ConceptsPandemicsAerosolsAir PollutantsMetals, HeavyParticulate MatterAirborne particle-bound metalsBack propagation artificial neural networkHealth riskSimulationSupport vector machine

Identifiers

PMID32721685
PMCPMC7340598
OpenAlexW3038966175

What OpenQuestion holds

Textmetadata
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.