Evidence map›Paper›PMID 33884498›Full record

ArticleEnvironmental monitoring and assessment2021

Modeling of atmospheric particulate matters via artificial intelligence methods.

Pınar Cihan, Huseyin Ozel, Huseyin Kurtulus Ozcan

Abstract read
PubMed Publisher
In one paragraph

Article in Environmental monitoring and assessment, 2021. 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
1.5field-weighted citation impact, top 21% 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

0 citing papers in PubMed, 20 citations in OpenAlex.

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

3 authors at 2 institutions in 1 country.

Pınar CihanDepartment of Computer Engineering, Corlu Engineering Faculty, Tekirdag Namık Kemal University, 59860, Çorlu, Tekirdag, Turkey. pkaya@nku.edu.tr.ORCID http://orcid.org/0000-0001-7958-7251
Huseyin OzelEngineering Faculty, Department of Environmental Engineering, Istanbul University-Cerrahpasa, 34320, Avcilar, Istanbul, Turkey.
Huseyin Kurtulus OzcanEngineering Faculty, Department of Environmental Engineering, Istanbul University-Cerrahpasa, 34320, Avcilar, Istanbul, Turkey.
Istanbul University-Cerrahpaşa · TRTekirdağ Namık Kemal University · TR

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Nowadays, pollutants continue to be released into the atmosphere in increasing amounts with each passing day. Some of them may turn into more harmful forms by accumulating in different layers of the atmosphere at different times and can be transported to other regions with atmospheric events. Particulate matter (PM) is one of the most important air pollutants in the atmosphere, and it can be released into the atmosphere by natural and anthropogenic processes or can be formed in the atmosphere as a result of chemical reactions. In this study, it was aimed to predict PM

Indexed as

Air PollutantsParticulate MatterArtificial IntelligenceAtmosphereEnvironmental MonitoringAir PollutantsParticulate MatterArtificial intelligenceMachine learningMeteorological dataParticular matter

Identifiers

PMID33884498
OpenAlexW3153653243

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.