Farmers' Preferences for Gene Editing Crops and Influencing Factors
ABSTRACT Gene editing (GE) is gaining momentum worldwide, but limited data on UK farmers' preferences hinders our understanding of its potential impact amid deregulation debates. Based on a survey of 200 English arable farmers, we employ a Latent Class Analysis and Multinomial Logit regressions to investigate current preferences for GE crops.
Bertolozzi‐Caredio Daniele +1 more
wiley +1 more source
Simulated evaluation of large language model stepwise diagnostic reasoning with real-world chest pain encounters and Bayesian networks. [PDF]
Safranek CW +7 more
europepmc +1 more source
Impact of Trade Protectionism on Economic Growth Based on Bayesian Networks and Fuzzy Logic
Yan Li
openalex +2 more sources
Macro Programming through Bayesian Networks: Distributed Inference and Anomaly Detection
Marco Mamei, Radhika Nagpal
openalex +2 more sources
ABSTRACT This paper examines the relationship between participation in the EU Rural Development Program and the economic performance of Italian olive farms using a finite‐mixture model with inverse‐probability‐weighted regression adjustment. Based on 2010–2022 FADN panel data, it estimates heterogeneous treatment effects while correcting for selection ...
Francesco Caracciolo, Marilena Furno
wiley +1 more source
Improving Sepsis Prediction in the ICU with Explainable Artificial Intelligence: The Promise of Bayesian Networks. [PDF]
Agard G +5 more
europepmc +1 more source
Model Based on Bayesian Networks for Monitoring Events in a Supply Chain
Erica Fernández +2 more
openalex +2 more sources
Topological Properties of International Commodity Market: How Uncertainty Affects the Linkages?
ABSTRACT The study aims to explore the network topology of the international commodity market by examining the interconnections among 21 commodity futures across various categories, including energy, precious and industrial metals, and agriculture. We analyze the market structure of these commodity futures under both low and high uncertainty conditions
Ibrahim Yagli, Bayram Deviren
wiley +1 more source
Data-driven Bayesian networks for risk scenario mapping of Falls from height accidents. [PDF]
Li J, Wang T.
europepmc +1 more source

