ArticleSensors (Basel, Switzerland)2020
Application of Machine Learning for the in-Field Correction of a PM
Article in Sensors (Basel, Switzerland), 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.
- GEMS satellite data fusion for hourly air quality prediction in Taiwan.Scientific reports · 2026Article
- Dynamic calibration of low-cost PMNPJ climate and atmospheric science · 2025Article
- Investigating Use of Low-Cost Sensors to Increase Accuracy and Equity of Real-Time Air Quality Information.Environmental science & technology · 2023Article
- Calibration of a Stereoscopic Vision System in the Presence of Errors in Pitch Angle.Sensors (Basel, Switzerland) · 2022Article
- Building Low-Cost Sensing Infrastructure for Air Quality Monitoring in Urban Areas Based on Fog Computing.Sensors (Basel, Switzerland) · 2022Article
- Developing Relative Humidity and Temperature Corrections for Low-Cost Sensors Using Machine Learning.Sensors (Basel, Switzerland) · 2021Article
- Multi-Sensor Information Ensemble-Based Automatic Parking System for Vehicle Parallel/Nonparallel Initial State.Sensors (Basel, Switzerland) · 2021Article
- A Review of Low-Cost Particulate Matter Sensors from the Developers' Perspectives.Sensors (Basel, Switzerland) · 2020Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors.
Funding
Abstract
Many low-cost sensors (LCSs) are distributed for air monitoring without any rigorous calibrations. This work applies machine learning with 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.