85 papers
This study demonstrates that recalculating journal impact factors by excluding extreme citation outliers from the document sample, with an optimal retention threshold of 90%, effectively reduces indicator fluctuations and enhances the stability and rationality of journal evaluation systems.
This paper demonstrates that a network's variance-weighted social power (F) simultaneously dictates the minimum information cost required to steer a group's consensus to a false value and the difficulty of detecting such an attack, revealing that concentrating influence to improve collective accuracy inherently increases the network's vulnerability to undetectable manipulation.
This paper introduces Sketch-FORCE, a sub-quadratic streaming algorithm that combines robust scale tracking with Frequent Directions matrix sketching to enable efficient, memory-light covariance estimation for high-dimensional data under heavy-tailed contamination and adversarial outliers.
This study evaluates a proportionate validation framework for AI-assisted data extraction using Elicit within a health scoping review, demonstrating that high agreement between AI and human extraction (AC2 = 0.960) supports the use of structured human-in-the-loop workflows as a reliable and scalable alternative to full dual manual extraction.
Using causal machine learning on over 500,000 UK crash records, this study estimates that roads with speed limits of 50 mph or higher increase the likelihood of fatal or serious accidents by approximately 6–7 percentage points, with these effects being most pronounced during daytime under dry and favorable conditions.