ArticleScientific reports2023
Estimating PM
Article in Scientific reports, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers, 1 of them a synthesis that pooled 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.
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.
Who cites it
7 citing papers in PubMed, 1 synthesis or guideline pooled it, 37 citations in OpenAlex.
- Prediction accuracy of available early warning systems for air pollution across WHO South-East Asia region: a systematic review.Frontiers in public health · 2026Pooled it
- Modified resampling strategy for extreme values in imbalanced air pollution data using moving block bootstrapping approach with relevance weighting (MBB-RW).Scientific reports · 2025Article
- PMScientific reports · 2025Article
- Individual cardiorespiratory fitness exercise prescription for older adults based on a back-propagation neural network.Frontiers in public health · 2025Article
- Prediction of Daily PMEnvironmental health insights · 2025Article
- Prediction of COD in industrial wastewater treatment plant using an artificial neural network.Scientific reports · 2024Article
- Exploring the spatiotemporal patterns of county-scale PM2.5 drivers in Shandong Province from 2000 to 2020.PloS one · 2024Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors at 4 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The accurate prediction of air pollutants, particularly Particulate Matter (PM), is critical to support effective and persuasive air quality management. Numerous variables influence the prediction of PM, and it's crucial to combine the most relevant input variables to ensure the most dependable predictions. This study aims to address this issue by utilizing correlation coefficients to select the most pertinent input and output variables for an air pollution model. In this work, PM
Identifiers
What OpenQuestion holds
Registered trials
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.