Mackenzie, E., et al. Hunting for New Glitches in LIGO Data Using Community Science. 2025. arXiv, 2025, doi:10.48550/arXiv.2508.13923.
Jackson, Corey Brian, et al. “Leveling up or Dropping Out: Searching for Learning Routines in Crowdsourced Environments”. Proceedings of the ACM on Human-Computer Interaction, CSCW, 2025, doi:10.1145/3757489.
Wu, Yunan, et al. “Advancing Glitch Classification in Gravity Spy: Multi-View Fusion With Attention-Based Machine Learning for Advanced LIGO’s Fourth Observing Run”. Classical and Quantum Gravity, 2025, doi:10.1088/1361-6382/adf58b.
Jackson, Corey. “Please Say ‘shibboleth’: Socialization through Language Adoption in Virtual Citizen Science”. 2025. Proceedings of the International AAAI Conference on Web and Social Media, vol. 19, 2025, pp. 885-98, doi:10.1609/icwsm.v19i1.35851.
Fortson, Lucy, et al. “Artificial Intelligence and the Future of Citizen Science”. Citizen Science: Theory and Practice, vol. 9, 1, 2024, doi:10.5334/cstp.738.
Bullard, Julia, et al. “Folksonomies in Crowdsourcing Platforms: Three Tensions Associated With the Development of Shared Language in Distributed Groups”. The European Conference on Computer-Supported Cooperative Work (ECSCW), 2024, doi:10.48340/ecscw2024_n06.
Zevin, Michael, et al. “Gravity Spy: Lessons Learned and a Path Forward”. 2024. European Physical Journal Plus, vol. 139, 2024, p. Article 100, doi:10.1140/epjp/s13360-023-04795-4.
Østerlund, Carsten, et al. “Mutual Learning in Human-AI Interaction”. Trust and Reliance in Evolving Human-AI Workflows (TREW) Workshop, ACM CHI Conference, 2024.
Østerlund, Carsten, et al. “Supporting and Augmenting Human and Machine Learning in Citizen Science: Lessons from Gravity Spy”. 2024. Citizen Science: Theory and Practice, vol. 9, no. 1, 2024, p. 42, doi:10.5334/cstp.738.