Vetter, V. M., Drewelies, J., Homann, J., Düzel, S., Deecke, L., Jawinski, P., Kühn, S., Kubala, E., Markett, S., Mülleder, M., Ralser, M., Lindenberger, U., Lill, C. M., Gerstorf, D., Bertram, L., & Demuth, I. (2025). Comprehensive comparison of sixteen markers of biological aging: Cross-sectional and longitudinal results from the Berlin Aging Study II (BASE-II). MedRxiv, April 10, 2025. https://doi.org/10.1101/2025.04.09.25325514

Vidal-Piñeiro, D., Sørensen, Ø., Strømstrad, M., Amlien, I. K., Baaré, W., Bartrés-Faz, D., Brandmaier, A. M., Cattaneo, G., Düzel, S., Ghisletta, P., Henson, R. N., Kühn, S., Lindenberger, U., Mowinckel, A. M., Nyberg, L., Pascual-Leone, A., Roe, J. M., Solana-Sánchez, J., Solé-Padullés, C., Watne, L. O., Wolfers, T., the Vietnam Era Twin Study of Aging (VETSA), the Australian Imaging Biomarkers and Lifestyle flagship study of ageing (AIBL), the Alzheimer's Disease Neuroimaging Initiative (ADNI), Walhovd, K. B., & Fjell, A. M. (2025). Vulnerability to memory decline in aging: A mega-analysis of structural brain change. BioRxiv, March 28, 2025. https://doi.org/10.1101/2025.03.27.642988

Wegwarth, O., Balzer, F., Boie, S. D., Giesa, N., Müller, A., Woike, J. K., Spies, C., & Giese, H. (2025). Leveraging fast-and-frugal trees in a multi-model framework to predict postoperative delirium from routine clinical data. OSF Preprints, January 22, 2025. https://doi.org/10.31219/osf.io/kn6sm

Willems, Y. E., Rezaki, A. D., Aikins, M., Bahl, A., Wu, Q., Belsky, D. W., & Raffington, L. (2025). Social determinants of health and epigenetic clocks: Meta-analysis of 140 studies. MedRxiv, May 08, 2025. https://doi.org/10.1101/2025.05.08.25327207

Zhong, Q., Jacoby, N., Tchernichovski, O., & Frey, S. (2025). Institutional preferences in the laboratory. arXiv, 2502.06748. https://doi.org/10.48550/arXiv.2502.06748

Zhou, Q., Liao, W., Allegrini, A. G., Rimfeld, K., Wertz, J., Morris, T., Raffington, L., Plomin, R., & Malanchini, M. (2025). From genetic disposition to academic achievement: The mediating role of non-cognitive skills across development. BioRxiv, February 27, 2025. https://doi.org/10.1101/2025.02.27.640510

Aeschbach, S., Mata, R., & Wulff, D. U. (2024). Measuring individual semantic networks: A simulation study. arXiv, 2410.18326. https://doi.org/10.48550/arXiv.2410.18326

Analytis, P. P., Kaushik, K., Herzog, S. M., Bahrami, B., & Deroy, O. (2024). A recommender-network perspective on the informational value of critics and crowds. arXiv, 2403.18868. https://doi.org/10.48550/arXiv.2403.18868

Awad, E., Yoeli, E., Rahwan, I., & Rahwan, Z. (2024). Heterogeneity in charitable giving preferences from over 2 million decisions worldwide. OSF Preprints, September 11, 2024. https://doi.org/10.31219/osf.io/28g3z

Beck, E. D., Willroth, E. C., Delius, J. A. M., Bennett, D. A., Barnes, L. L., James, B. D., Lipton, R. B., Katz, M., Hassing, L. B., Huisman, M., Mroczek, D. K., & Graham, E. K. (2024). A taxonomy of data synthesis: A tutorial. PsyArXiv, March 9, 2024. https://doi.org/10.31234/osf.io/m3ywe

Berger, J., Moussaïd, M., Hertwig, R., Herzog, S. M., & Kurvers, R. H. J. M. (2024). Making the wisdom of crowds efficient: With confidence. PsyArXiv, November 12, 2024. https://doi.org/10.31234/osf.io/j9t6p

Blonski, M., Eibelshäuser, S., Hegemann, H., Klockmann, V., & von Schenk, A. (2024). Human and algorithmic cooperation: Parameters matter! (Version posted online November 28, 2024). SSRN eLibrary, October 21, 2024. https://doi.org/10.2139/ssrn.4955708

Born, F., & Spitzer, B. (2024). Long-term effects of working memory retrieval from prioritized and deprioritized states (Version posted online November 28, 2024). BioRxiv, October 11, 2024. https://doi.org/10.1101/2024.10.08.617145

de Gee, J. W., Kloosterman, N. A., Braun, A., & Donner, T. H. (2024). Catecholamines reduce choice history biases. BioRxiv, Oktober 28, 2024. https://doi.org/10.1101/2024.10.28.620689

Dong, M., Bonnefon, J.-F., & Rahwan, I. (2024). False consensus biases AI against vulnerable stakeholders. SSRN eLibrary, June 28, 2024. https://doi.org/10.2139/ssrn.4876227

Donoghue, T., Hammonds, R., Lybrand, E., Waschke, L., Gao, R., & Voytek, B. (2024). Evaluating and comparing measures of aperiodic neural activity. BioRxiv, September 15, 2024. https://doi.org/10.1101/2024.09.15.613114

Droop, S., Oranç, C., Bramley, N. R., & Ruggeri, A. (2024). Inverting the Turing test to track changing intuitions about artificial minds. PsyArXiv, October 09, 2024. https://doi.org/10.31234/osf.io/ge72j

Ferrari, A. E. V., Gupta, P., & Iqbal, N. (2024). Machine learning and optimization-based approaches to duality in statistical physics. arXiv, 2411.04838. https://doi.org/10.48550/arXiv.2411.04838

Fuławka, K., & Pachur, T. (2024). Beyond lotteries: An affect-based computational framework for modeling risky choices with nonmonetary outcomes. PsyArXiv, November 28, 2024. https://doi.org/10.31234/osf.io/xj4ez

Ganesh, P., Cichy, R. M., Schuck, N. W., Finke, C., & Bruckner, R. (2024). Adaptive integration of perceptual and reward information in an uncertain world. BioRxiv, April 28, 2024. https://doi.org/10.1101/2024.04.24.590947