Impacts of meteorological variables and machine learning algorithms on rice yield prediction in Korea.

As crop productivity is greatly influenced by weather conditions, many attempts have been made to estimate crop yields using meteorological data and have achieved great progress with the development of machine learning. However, most yield prediction models are developed based on observational data, and the utilization of climate model output in yield prediction has been addressed in very few studies. In this study, we estimate rice yields in South Korea using the meteorological variables provided by ERA5 reanalysis data (ERA-O) and its dynamically downscaled data (ERA-DS).

Elaborations and Denials in Children's Responses to Yes-No Any/Some Questions in Forensic Interviews.

This study examined 379 4- to 12-year-old children's answers to any/some and other yes-no questions in forensic interviews about sexual abuse ( = 10,041). Yes-no questions that include the terms any/some (e.g.