96 research outputs found
Machine Learning Outperforms Regression Analysis to Predict Next-Season Major League Baseball Player Injuries: Epidemiology and Validation of 13,982 Player-Years From Performance and Injury Profile Trends, 2000-2017
Background: Machine learning (ML) allows for the development of a predictive algorithm capable of imbibing historical data on a Major League Baseball (MLB) player to accurately project the player\u27s future availability.
Purpose: To determine the validity of an ML model in predicting the next-season injury risk and anatomic injury location for both position players and pitchers in the MLB.
Study Design: Descriptive epidemiology study.
Methods: Using 4 online baseball databases, we compiled MLB player data, including age, performance metrics, and injury history. A total of 84 ML algorithms were developed. The output of each algorithm reported whether the player would sustain an injury the following season as well as the injury\u27s anatomic site. The area under the receiver operating characteristic curve (AUC) primarily determined validation.
Results: Player data were generated from 1931 position players and 1245 pitchers, with a mean follow-up of 4.40 years (13,982 player-years) between the years of 2000 and 2017. Injured players spent a total of 108,656 days on the disabled list, with a mean of 34.21 total days per player. The mean AUC for predicting next-season injuries was 0.76 among position players and 0.65 among pitchers using the top 3 ensemble classification. Back injuries had the highest AUC among both position players and pitchers, at 0.73. Advanced ML models outperformed logistic regression in 13 of 14 cases.
Conclusion: Advanced ML models generally outperformed logistic regression and demonstrated fair capability in predicting publicly reportable next-season injuries, including the anatomic region for position players, although not for pitchers
Field Guide for the Geology of Central Park and New York City
Teachers guide for geology of Central Park. Supplement to: Jaret, S. J., et. al. (2021). Geology of Central Park, Manhattan, New York City, USA: New geochemical insights. Geological Society of America bulletin. https://doi.org/10.1130/2020.0061(02
SNEWS: The SuperNova Early Warning System
This paper provides a technical description of the SuperNova Early Warning
System (SNEWS), an international network of experiments with the goal of
providing an early warning of a galactic supernova.Comment: 25 pages, for New Journal of Physics Focus Issue on Neutrino Physic
The Long-Baseline Neutrino Experiment: Exploring Fundamental Symmetries of the Universe
The preponderance of matter over antimatter in the early Universe, the
dynamics of the supernova bursts that produced the heavy elements necessary for
life and whether protons eventually decay --- these mysteries at the forefront
of particle physics and astrophysics are key to understanding the early
evolution of our Universe, its current state and its eventual fate. The
Long-Baseline Neutrino Experiment (LBNE) represents an extensively developed
plan for a world-class experiment dedicated to addressing these questions. LBNE
is conceived around three central components: (1) a new, high-intensity
neutrino source generated from a megawatt-class proton accelerator at Fermi
National Accelerator Laboratory, (2) a near neutrino detector just downstream
of the source, and (3) a massive liquid argon time-projection chamber deployed
as a far detector deep underground at the Sanford Underground Research
Facility. This facility, located at the site of the former Homestake Mine in
Lead, South Dakota, is approximately 1,300 km from the neutrino source at
Fermilab -- a distance (baseline) that delivers optimal sensitivity to neutrino
charge-parity symmetry violation and mass ordering effects. This ambitious yet
cost-effective design incorporates scalability and flexibility and can
accommodate a variety of upgrades and contributions. With its exceptional
combination of experimental configuration, technical capabilities, and
potential for transformative discoveries, LBNE promises to be a vital facility
for the field of particle physics worldwide, providing physicists from around
the globe with opportunities to collaborate in a twenty to thirty year program
of exciting science. In this document we provide a comprehensive overview of
LBNE's scientific objectives, its place in the landscape of neutrino physics
worldwide, the technologies it will incorporate and the capabilities it will
possess.Comment: Major update of previous version. This is the reference document for
LBNE science program and current status. Chapters 1, 3, and 9 provide a
comprehensive overview of LBNE's scientific objectives, its place in the
landscape of neutrino physics worldwide, the technologies it will incorporate
and the capabilities it will possess. 288 pages, 116 figure
Identifying Shocked Feldspar on Mars Using Perseverance Spectroscopic Instruments : Implications for Geochronology Studies on Returned Samples
The Perseverance rover (Mars 2020) mission, the first step in NASA’s Mars Sample Return (MSR) program, will select samples for caching based on their potential to improve understanding Mars’ astrobiological, geological, geochemical, and climatic evolution. Geochronologic analyses will be among the key measurements planned for returned samples. Assessing a sample’s shock history will be critical because shock metamorphism could influence apparent sample age. Shock effects in one Mars-relevant mineral class, plagioclase feldspar, have been well-documented using various spectroscopy techniques (thermal infrared reflectance, emission, and transmission spectroscopy, Raman, and luminescence). A subset of these data will be obtained with the SuperCam and SHERLOC (Scanning Habitable Environments with Raman & Luminescence for Organics & Chemicals) instruments onboard Perseverance to inform caching decisions for MSR. Here, we review shock indicators in plagioclase feldspar as revealed in Raman, luminescence, and IR spectroscopy lab data, with an emphasis on Raman spectroscopy. We consider how this information may inform caching decisions for selecting optimal samples for geochronology measurements. We then identify challenges and make recommendations for both in situ measurements performed with SuperCam and SHERLOC and for supporting lab studies to enhance the success of geochronologic analyses after return to Earth
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Extreme isotopic heterogeneity in impact melt rocks: Implications for Martian meteorites
Lead isotope ratios have been determined in multiple feldspar grains from hand samples of impact melt rock at the Manicouagan and Sudbury impact structures in Canada. The results reveal an extreme range of isotope values. This indicates that melt sheets are not homogeneous with respect to Pb at the millimeter scale. Such heterogeneity is significantly larger than that seen in non-impact-generated igneous rocks. Individual Pb isotope ratios of feldspars from Martian shergottites show a large range in 206Pb/204Pb values within one sample, more similar to the terrestrial impact melt sheets than to nonimpact igneous rocks. We suggest crystallization from impact melt sheets rather than volcanic sources as a petrogenetic model for some of the Martian shergottites.12 month embargo; first published 07 February 2023This item from the UA Faculty Publications collection is made available by the University of Arizona with support from the University of Arizona Libraries. If you have questions, please contact us at [email protected]
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