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Dang, L.-X., Zhou, P., Sun, L., Mao, J., Vink, J., Zhang, Q.-Q., & Domček, V. (2024). Typing supernova remnant G352.7−0.1 using XMM–Newton X-ray observations. Monthly Notices of the Royal Astronomical Society, 529(4), 4117-4127. https://doi.org/10.1093/mnras/stae805 -
He, D., Artzy-Randrup, Y., Musa, S. S., Gräf, T., Naveca, F., & Stone, L. (2024). Modelling the unexpected dynamics of COVID-19 in Manaus, Brazil. Infectious Disease Modelling, 9(2), 557–568. https://doi.org/10.1016/j.idm.2024.02.012 -
van der Goot, M. J., Koubayová, N., & van Reijmersdal, E. A. (2024). Understanding users’ responses to disclosed vs. undisclosed customer service chatbots: A mixed methods study. AI & Society, 39(6), 2947–2960. https://doi.org/10.1007/s00146-023-01818-7 -
Nath, S. S., Dayan, P., & Stevenson, C. (2024). Characterising the Creative Process in Humans and Large Language Models. In K. Grace, M. T. Llano, P. Martins, & M. Hedblom (Eds.), Proceedings of the Fifteenth International Conference on Computational Creativity: ICCC'24 : Jönköping, Sweden, 17-21 June (pp. 325-330). Article 179 Association for Computational Creativity. https://doi.org/10.48550/arXiv.2405.00899 -
Hickey, C. (2024). Suficiencia, límites y perspectivas de umbrales múltiples. In I. Robeyns (Ed.), Tener Demasiado: Ensayos Filosóficos sobre el Limitarismo (pp. 245-276). Open Book Publishers. https://doi.org/10.11647/OBP.0354.09 -
Isailović, I. (2024). Introduction: critical legal approaches in EU law—reflections on new research directions. Transnational Legal Theory, 15(4), 493-499. https://doi.org/10.1080/20414005.2024.2439675 -
Ohme, J., Araujo, T., Boeschoten, L., Freelon, D., Ram, N., Reeves, B. B., & Robinson, T. B. (2024). Digital Trace Data Collection for Social Media Effects Research: APIs, Data Donation, and (Screen) Tracking. Communication Methods and Measures, 18(2), 124-141. https://doi.org/10.1080/19312458.2023.2181319 -
Háden, G. P., Bouwer, F. L., Honing, H., & Winkler, I. (2024). Beat processing in newborn infants cannot be explained by statistical learning based on transition probabilities. Cognition, 243, Article 105670. https://doi.org/10.1016/j.cognition.2023.105670
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