43 citations
Counting papers with at most 25 authors, so collaboration author lists do not stand in for the people here.
- Syngenta (United Kingdom)GB2 papers
- BI Norwegian Business SchoolNO1 paper
- Courant Institute of Mathematical SciencesUS1 paper
- Imperial College LondonGB1 paper
- Kennesaw State UniversityUS1 paper
- New York UniversityUS1 paper
- Syngenta (United States)US1 paper
- University of MilanIT1 paper
- University of MissouriUS1 paper
- University of North Carolina at Chapel HillUS1 paper
- University of YorkGB1 paper
5 papers
Navigating the muddy waters of bias in artificial intelligence research: Understanding divergent meanings and conceptions
Mohammad Hossein Jarrahi, Amir Karami, Patrick Conway +2
As artificial intelligence (AI) pervades many decision-making domains, AI bias grows in importance. Although there is increasing awareness of the social and ethical consequences of…
Toward precision soil health: A regional framework for site-specific management across Missouri
Dipal Shah, Jordon Wade, Timothy Haithcoat +2
Effective soil health management is crucial for sustaining agriculture, adopting ecosystem resilience, and preserving water quality. However, Missouri's diverse landscapes limit th…
Estimating random close packing in polydisperse and bidisperse hard spheres via an equilibrium model of crowding
Carmine Anzivino, Mathias Casiulis, Tom Zhang +3
We show that an analogy between crowding in fluid and jammed phases of hard spheres captures the density dependence of the kissing number for a family of numerically generated jamm…
Physics-Informed Deep Learning Characterizes Morphodynamics of Asian Soybean Rust Disease
Henry Cavanagh, Andreas Mosbach, Gabriel Scalliet +2
Medicines and agricultural biocides are often discovered using large phenotypic screens across hundreds of compounds, where visible effects of whole organisms are compared to gauge…
Considerations for using reproduction data in toxicokinetic-toxicodynamic modelling
Tjalling Jager, Marie Trijau, Neil Sherborne +2
Toxicokinetic-toxicodynamic (TKTD) modelling is essential to make sense of the time dependence of toxic effects, and to interpret and predict consequences of time-varying exposure.…