Researchers have created a prediction method that comes startlingly close to real-world results. It works by aiming for strong alignment with actual values rather than simply reducing mistakes. Tests ...
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Kalshi may be more useful than some traditional economic forecasting methods, Fed researchers find
The Fed paper found that Kalshi's markets provide data that's "valuable to both researchers and policymakers." ...
Figure 1. This figure depicts the four categories of protein druggability target screening tools discussed in this section, which include structure-based methods, sequence-based methods, machine ...
Google's DeepMind just released WeatherNext 2, a new version of its AI weather prediction model. The company promises that it "delivers more efficient, more accurate and higher-resolution global ...
AI models outperform traditional statistics in predicting post-complete cytoreduction outcomes in ovarian cancer patients. AI's diagnostic accuracy was high for predicting overall survival and no ...
In the rapidly advancing field of computational biology, a newly peer-reviewed review explores the transformative role of deep learning techniques in revolutionizing protein structure prediction. The ...
Data assimilation is an important mathematical discipline in earth sciences, particularly in numerical weather prediction (NWP). However, conventional data assimilation methods require significant ...
Heart failure is a leading cause of hospitalization and long-term disability, with many individuals progressing from subclinical disease to overt symptoms ...
A new report from the Federal Reserve indicates that prediction markets can be a valuable tool for researchers and policymakers in terms of providing rich, frequently updated probabilities regarding ...
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