Evidence map›Paper›PMID 35682517›Full record

ArticleInternational journal of environmental research and public health2022

Machine Learning and Meteorological Normalization for Assessment of Particulate Matter Changes during the COVID-19 Lockdown in Zagreb, Croatia.

Mario Lovrić, Mario Antunović, Iva Šunić, Matej Vuković, Simonas Kecorius, Mark Kröll, Ivan Bešlić, Ranka Godec, Gordana Pehnec, Bernhard C Geiger and 2 more

Abstract read
In one paragraph

Article in International journal of environmental research and public health, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing 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

6 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Article
  5. A Study of Urban Haze and Its Association with Cold Surge and Sea Breeze for Greater Bangkok.International journal of environmental research and public health · 2023
    Article
  6. Prediction of Particulate Concentration Based on Correlation Analysis and a Bi-GRU Model.International journal of environmental research and public health · 2022
    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

12 authors.

Mario LovrićKnow-Center, Inffeldgasse 13, 8010 Graz, Austria.ORCID 0000-0002-3541-9624
Mario AntunovićAscalia d.o.o., Ulica Trate 16, 40000 Čakovec, Croatia.
Iva ŠunićInstitute for Anthropological Research, Gajeva 32, 10000 Zagreb, Croatia.ORCID 0000-0002-5289-9463
Matej VukovićPro2Future GmbH, Inffeldgasse 25F, 8010 Graz, Austria.
Simonas KecoriusInstitute of Epidemiology, Helmholtz Zentrum München, Ingolstädter Landstr. 1, 85764 Neuherberg, Germany.
Mark KröllKnow-Center, Inffeldgasse 13, 8010 Graz, Austria.
Ivan BešlićEnvironmental Hygiene Unit, Institute for Medical Research and Occupational Health, Ksaverska cesta 2, 10000 Zagreb, Croatia.
Ranka GodecEnvironmental Hygiene Unit, Institute for Medical Research and Occupational Health, Ksaverska cesta 2, 10000 Zagreb, Croatia.ORCID 0000-0001-8441-1103
Gordana PehnecEnvironmental Hygiene Unit, Institute for Medical Research and Occupational Health, Ksaverska cesta 2, 10000 Zagreb, Croatia.
Bernhard C GeigerKnow-Center, Inffeldgasse 13, 8010 Graz, Austria.ORCID 0000-0003-3257-743X
Stuart K GrangeEmpa, Swiss Federal Laboratories for Materials Science and Technology, 8600 Dübendorf, Switzerland.
Iva ŠimićEnvironmental Hygiene Unit, Institute for Medical Research and Occupational Health, Ksaverska cesta 2, 10000 Zagreb, Croatia.ORCID 0000-0002-6641-106X

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

In this paper, the authors investigated changes in mass concentrations of particulate matter (PM) during the Coronavirus Disease of 2019 (COVID-19) lockdown. Daily samples of PM

Indexed as

Air PollutantsAir PollutionCOVID-19Bayes TheoremCitiesCommunicable Disease ControlCroatiaEnvironmental MonitoringHumansMachine LearningParticulate MatterAir PollutantsParticulate Matterair qualitycoronavirus disease of 2019LightGBMPM1PM10PM2.5random foreststraffic

Identifiers

PMID35682517
PMCPMC9180289

What OpenQuestion holds

Textmetadata
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.