Evidence map›Paper›PMID 37637795›Full record

ArticleFrontiers in public health2023

Construction and evaluation of hourly average indoor PM

Yewen Shi, Zhiyuan Du, Jianghua Zhang, Fengchan Han, Feier Chen, Duo Wang, Mengshuang Liu, Hao Zhang, Chunyang Dong, Shaofeng Sui

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Frontiers in public health, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Personal PMToxics · 2026
    Article
  2. Review
  3. 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

10 authors.

Yewen ShiShanghai Municipal Center for Disease Control and Prevention, Shanghai, China.
Zhiyuan DuDepartment of Environmental Health, Key Laboratory of the Public Health Safety, Ministry of Education, School of Public Health, Fudan University, Shanghai, China.
Jianghua ZhangShanghai Municipal Center for Disease Control and Prevention, Shanghai, China.
Fengchan HanShanghai Municipal Center for Disease Control and Prevention, Shanghai, China.
Feier ChenShanghai Municipal Center for Disease Control and Prevention, Shanghai, China.
Duo WangShanghai Municipal Center for Disease Control and Prevention, Shanghai, China.
Mengshuang LiuShanghai Municipal Center for Disease Control and Prevention, Shanghai, China.
Hao ZhangDepartment of Environmental Health, Key Laboratory of the Public Health Safety, Ministry of Education, School of Public Health, Fudan University, Shanghai, China.
Chunyang DongShanghai Municipal Center for Disease Control and Prevention, Shanghai, China.
Shaofeng SuiShanghai Municipal Center for Disease Control and Prevention, Shanghai, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: People usually spend most of their time indoors, so indoor fine particulate matter (PM Methods: In this study, based on the monitoring data of multiple types of places, the classical multiple linear regression (MLR) method and random forest regression (RFR) algorithm of machine learning were used to develop hourly average indoor PM Results: The final predictor variables incorporated in the MLR model were outdoor PM Conclusion: In this research, hourly average indoor PM

Indexed as

Air PollutantsAlgorithmsDatabases, FactualHumansParticulate MatterSeasonsAir PollutantsParticulate Matterindoor air qualitymachine learningPM2.5prediction modelsrandom forest

Identifiers

PMID37637795
PMCPMC10447970

What OpenQuestion holds

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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 OpenQuestion graph.