benchmarks sourced from publicly available material carry contamination risk, where training-data exposure can silently inflate scores.
大多数人认为公开数据集是AI评估的金标准，能够提供客观公正的测试环境。但作者警告，使用公开材料构建的基准测试存在污染风险，训练数据接触会悄无声息地提高分数。这一观点挑战了AI评估领域的传统做法，暗示我们需要更严格的数据隔离措施或转向私有数据集进行评估。
Jørgensen, F. J., Nielsen, L. H., & Petersen, M. B. (2021). Willingness to Take the Booster Vaccine in a Nationally Representative Sample of Danes. PsyArXiv. https://doi.org/10.31234/osf.io/wurz8
Mackay, A. I. M. & PhD. (2022, January 29). Thank goodness we did all the work. Virology Down Under. https://virologydownunder.com/thank-goodness-we-did-all-the-work/
Patone, M., Mei, X. W., Handunnetthi, L., Dixon, S., Zaccardi, F., Shankar-Hari, M., Watkinson, P., Khunti, K., Harnden, A., Coupland, C. A., Channon, K. M., Mills, N. L., Sheikh, A., & Hippisley-Cox, J. (2021). Risk of myocarditis following sequential COVID-19 vaccinations by age and sex (p. 2021.12.23.21268276). medRxiv. https://doi.org/10.1101/2021.12.23.21268276
Iacobucci, G. (2021). Covid-19 and pregnancy: Vaccine hesitancy and how to overcome it. BMJ, 375, n2862. https://doi.org/10.1136/bmj.n2862
Frost, M. (n.d.). Busting COVID-19 vaccination myths. Retrieved November 2, 2021, from https://acpinternist.org/archives/2021/11/busting-covid-19-vaccination-myths.htm
Padilla, L., Hosseinpour, H., Fygenson, R., Howell, J., Chunara, R., & Bertini, E. (2021). Effects of COVID-19 Uncertainty Visualizations on Novice Risk Estimates. PsyArXiv. https://doi.org/10.31234/osf.io/6axc7
What is behind the low covid-19 vaccine take-up in some ethnic minorities? - The BMJ. (n.d.). Retrieved June 27, 2021, from https://blogs.bmj.com/bmj/2021/04/08/what-is-behind-the-low-covid-19-vaccine-take-up-in-some-ethnic-minorities/?utm_source=twitter&utm_medium=social&utm_term=hootsuite&utm_content=sme&utm_campaign=usage
Deepti Gurdasani on Twitter: “I’m still utterly stunned by yesterday’s events—Let me go over this in chronological order & why I’m shocked. - First, in the morning yesterday, we saw a ‘leaked’ report to FT which reported on @PHE_uk data that was not public at the time🧵” / Twitter. (n.d.). Retrieved June 27, 2021, from https://twitter.com/dgurdasani1/status/1396373990986375171
Guglielmi, G. (2020). Coronavirus and public holidays: What the data say. Nature, 588(7839), 549–549. https://doi.org/10.1038/d41586-020-03545-1
A hidden success in the Covid-19 mess: The internet. (2020, November 11). STAT. https://www.statnews.com/2020/11/11/a-hidden-success-in-the-covid-19-mess-the-internet/
AI and control of Covid-19 coronavirus. (n.d.). Artificial Intelligence. Retrieved October 15, 2020, from https://www.coe.int/en/web/artificial-intelligence/ai-and-control-of-covid-19-coronavirus
Holman, E. A., Thompson, R. R., Garfin, D. R., & Silver, R. C. (2020). The unfolding COVID-19 pandemic: A probability-based, nationally representative study of mental health in the U.S. Science Advances, eabd5390. https://doi.org/10.1126/sciadv.abd5390
Rauschenberg, C., Schick, A., Goetzl, C., Röhr, S., Riedel-Heller, S., Koppe, G., Durstewitz, D., Krumm, S., & Reininghaus, U. (2020). Social isolation, mental health and use of digital interventions in youth during the COVID-19 pandemic: A nationally representative survey [Preprint]. PsyArXiv. https://doi.org/10.31234/osf.io/v64hf
Groarke, J., Berry, E., Wisener, L.-G., McKenna-Plumley, P., McGlinchey, E., & Armour, C. (2020). Loneliness in the UK during the COVID-19 pandemic: Cross-sectional results from The COVID-19 Psychological Wellbeing Study [Preprint]. PsyArXiv. https://doi.org/10.31234/osf.io/j2pce
Raleigh, V. S. (2020). Tackling UK’s mortality problem: Covid-19 and other causes. BMJ, 369. https://doi.org/10.1136/bmj.m2295
Gozzi, N., Tizzani, M., Starnini, M., Ciulla, F., Paolotti, D., Panisson, A., & Perra, N. (2020). Collective response to the media coverage of COVID-19 Pandemic on Reddit and Wikipedia. ArXiv:2006.06446 [Physics]. http://arxiv.org/abs/2006.06446
Bostrom, A., Böhm, G., O’Connor, R. E., Hanss, D., Bodi-Fernandez, O., & Halder, P. (2020). Comparative risk science for the coronavirus pandemic. Journal of Risk Research, 0(0), 1–10. https://doi.org/10.1080/13669877.2020.1756384
Gao, S., Rao, J., Kang, Y., Liang, Y., & Kruse, J. (2020). Mapping county-level mobility pattern changes in the United States in response to COVID-19. ArXiv:2004.04544 [Physics, q-Bio]. http://arxiv.org/abs/2004.04544