ArticleAtmosphere2020
Application of Bayesian Additive Regression Trees for Estimating Daily Concentrations of PM
Article in Atmosphere, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
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
8 citing papers in PubMed.
- Tailoring Bayesian Additive Regression Trees (BART) for environmental mixture studies.PloS one · 2026Article
- Ranking factors across multiple domains in predicting adolescent mental health: a Bayesian machine learning approach.Child and adolescent psychiatry and mental health · 2025Article
- Probabilistic forecasting of hand, foot and mouth disease in Mainland China using Bayesian additive regression tree model.Scientific reports · 2025Article
- Quantifying the uncertainty of human activity recognition using a Bayesian machine learning method: a prediction study.Physical activity and nutrition · 2025Article
- Modified tree-based selection in hierarchical mixed-effect models with trees: A simulation study and real-data application.MethodsX · 2025Article
- Bayesian additive tree ensembles for composite quantile regressions.Statistics and computing · 2025Article
- Evaluation of Model-Based PMEnvironmental science & technology · 2023Article
- Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors.
Funding
Abstract
Bayesian additive regression tree (BART) is a recent statistical method that combines ensemble learning and nonparametric regression. BART is constructed under a probabilistic framework that also allows for model-based prediction uncertainty quantification. We evaluated the application of BART in predicting daily concentrations of four fine particulate matter (PM
Indexed as
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.