ArticlePatterns (New York, N.Y.)2021
Digital twins of the natural environment.
Article in Patterns (New York, N.Y.), 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 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
6 citing papers in PubMed.
- Digitizing Dignity: Analyzing Digital Twins Through the Lens of Multidimensional Human Dignity.Bioethics · 2026Article
- Integrating biological and environmental data to solve key scientific and societal challenges.Bioscience · 2026Article
- Digital Twins in Agriculture: Orchestration and Applications.Journal of agricultural and food chemistry · 2024Review
- Towards Digital Twins of the Oceans: The Potential of Machine Learning for Monitoring the Impacts of Offshore Wind Farms on Marine Environments.Sensors (Basel, Switzerland) · 2023Article
- How to avoid a local epidemic becoming a global pandemic.Proceedings of the National Academy of Sciences of the United States of America · 2023Article
- Transforming agrifood production systems and supply chains with digital twins.NPJ science of food · 2022Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
1 author.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Digital twins emerged in the field of engineering but are now being applied in many areas of study. This article reflects on the enormous potential of digital twins of the natural environment and proposes an approach that builds on the massive legacy of process model understanding in this area combined with new insights from data understanding, including from AI/machine learning.
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.