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Classifying the unknown: Discovering novel gravitational-wave detector glitches using similarity learning. Physical Review D, 99(8), 082002. https://doi.org/10.1103/PhysRevD.99.082002
. (2019). Coordination theory: A ten-year retrospective. In , Human-Computer Interaction in Management Information Systems (pp. 120-138). M. E. Sharpe, Inc.
. (2006). CT Review to distribute.pdf (531.4 KB)Data quality up to the third observing run of Advanced LIGO: Gravity Spy glitch classifications. Classical And Quantum Gravity, 40(6). https://doi.org/10.1088/1361-6382/acb633
. (2023). Discovering features in gravitational-wave data through detector characterization, citizen science and machine learning. Classical And Quantum Gravity, 38(19). https://doi.org/10.1088/1361-6382/ac1ccb
. (2021). Gravity Spy: Integrating Advanced LIGO Detector Characterization, Machine Learning, and Citizen Science. Classical And Quantum Gravity, 34, 064003. https://doi.org/10.1088/1361-6382/aa5cea
. (2017). Gravity Spy: Lessons Learned and a Path Forward. European Physical Journal Plus, 139, Article 100. https://doi.org/10.1140/epjp/s13360-023-04795-4
. (2024). Knowledge Tracing to Model Learning in Online Citizen Science Projects. Ieee Transactions On Learning Technologies, 13, 123-134. https://doi.org/10.1109/TLT.2019.2936480
. (2020). transaction paper final figures in text.pdf (1.39 MB)Optimizing Features in Active Machine Learning for Complex Qualitative Content Analysis. In Workshop on Language Technologies and Computational Social Science, 52nd Annual Meeting of the Association for Computational Linguistics. Presented at the Workshop on Language Technologies and Computational Social Science, 52nd Annual Meeting of the Association for Computational Linguistics , Baltimore, MD.
. (2014). 9_Paper.pdf (195.46 KB)Teaching Citizen Scientists to Categorize Glitches using Machine-Learning-Guided Training. Computers In Human Behavior, 105, 106198. https://doi.org/10.1016/j.chb.2019.106198
. (2020). MLGT-preprint.pdf (2.43 MB)