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Novel machine-learning method produces detail

Scientists at the Cornell Lab of Ornithology have developed a novel way to model whether the populations of more than 500 bird species are increasing or decreasing. The method solves a nagging statistical problem by accounting for year-to-year changes in the behavior of people collecting the data. ....

Shawn Ligocki , Amanda Rodewald , Alison Johnston , Wesley Hochachka , Tom Auer , Chris Wood , Lauren Oldham Jaromczyk , Corin Robinson , Steve Kelling , Matthew Strimas Mackey , Daniel Fink , Cornell Lab Of Ornithology , Method Of Research , Cornell Lab , Double Machine , Machine Learning , Double Machine Learning , Double Machine Learning Trend Model , Citizen Science ,

AI Method Maps Population Trends for 550 Bird Species

AI Method Maps Population Trends for 550 Bird Species
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Tom Auer , Shawn Ligocki , Matthew Strimas Mackey , Lauren Oldham Jaromczyk , Chris Wood , Amanda Rodewald , Daniel Fink , Steve Kelling , Wesley Hochachka , Corin Robinson , Alison Johnston , Cornell Lab , Cornell Lab Of Ornithology , Double Machine , Machine Learning , Double Machine Learning , Double Machine Learning Trend Model , Citizen Science ,

2020 in review: COVID-19 was the story | Cornell Chronicle


2020 in review: COVID-19 was the story
December 21, 2020
The first mention of the word “coronavirus” in a Cornell Chronicle story in 2020 came on Jan. 29, when the university designated mainland China as an elevated-risk destination, and imposed travel restrictions on students, faculty and staff.
Since then, there have been more than 300 stories or university statements that mention COVID-19 posted on news.cornell.edu. It has been the story of the year.
The most-read Chronicle story of the year was a Weill Cornell Medicine-produced research FAQ from April 20, “Why is COVID-19 mild for some, deadly for others?” Given the fact that so much remains unknown about this mysterious virus, it’s no surprise that more than 60,000 readers – and counting – clicked on this story. ....

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