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Although Veniaminof Volcano in Alaska experiences frequent eruptions and has eight permanent seismic stations, only two of the past 13 eruptions have had precursory signals that prompted a pre-eruption warning from the Alaska Volcano Observatory (AVO) since 1993. Seismic data from Venianimof indicate that most eruptions from 2000 to 2018 do not coincide with increased seismicity. Additionally, analyses of InSAR data available from 2015 to 2018 which covers the pre-, syn-, and post-eruption periods of the 2018 eruption do not show clear signs of deformation. The systemic lack of systematic precursory signals raises critical questions about why some volcanoes do not exhibit clear unrest prior to eruption. Volcanoes that erupt frequently without precursory signals are often classified as “open” systems with magma migrating through an open network to eruption, rather than pausing at a shallow reservoir. However, the precursory signals, or lack thereof, from a small or deep closed magma system may be difficult to observe, resulting in a stealthy eruption mimicking the behavior of an open system. In this study, we utilize finite element, fluid injection models to investigate a hypothetical closed magma system at Veniaminof and evaluate its ability to erupt with no observable early-warning signals. Specifically, a series of numerical experiments are conducted to determine what model configurations lead to stealthy eruptions – i.e., producing ground deformation below the detection threshold for InSAR (<10 mm) and developing no seismicity, yet resulting in tensile failure which will promote diking and eruption. Model results indicate that the primary control on whether eruption precursors from deformation and seismicity will be present are the rheology of the host rock and the magma flux, followed by the secondary control of the size of the magma chamber, and then its depth and shape. Volcanoes with long-lived thermally mature magma systems with moderate to small magma reservoirs are the most likely to exhibit stealthy behavior, with the smallest systems most likely to fail without producing a deformation signal. This result is likely because small, deep magma systems produce minimal surface deformation and seismicity. For stealthy volcanoes like Veniaminof and others in Alaska (e.g., Cleveland, Shishaldin, Pavlof) and around the world, understanding the underlying magma system dynamics and their potential open vs. closed nature through numerical modeling is critical for providing robust forecasts of future eruptive activity. 

Abstract This article describes a novel method for quantifying fixation disparity and evaluates its role in visuospatial cognition during an authentic learning task, specifically, the determination of molecule chirality in organic chemistry involving mental rotation and pattern comparison. The first study examined the influence of molecular model dimensionality (2D vs. 3D) on chirality determination performance and visual attention of 55 participants. The second study explored how the sustained playing of the tile‐matching game Mahjong, a pattern comparison game, can affect visual attention and visuospatial performance during the chirality determination task of 59 participants. Fixation disparity was one of the eye tracking variables explored. Both studies revealed that (1) individuals with higher fixation disparity underperformed on the chirality task, which involves mental rotation and pattern comparison, and (2) fixation disparity improved over time in participants who played Mahjong. This work provides important implications for using fixation disparity as a possible biomarker of visuospatial performance.