机器学习正遭遇“可重复性危机”，或已成“炼金术”？(7)

[1] https://science-sciencemag-org.ezp-prod1.hul.harvard.edu/content/sci/365/6452/416.full.pdf
[2] https://research.fb.com/wp-content/uploads/2019/05/The-Scientific-Method-in-the-Science-of-Machine-Learning.pdf?
[3] https://bigdata-madesimple.com/machine-learning-disrupting-science-research-heres/
[4] https://biodatamining.biomedcentral.com/track/pdf/10.1186/s13040-018-0167-7
[5] https://www.sciencemag.org/news/2018/05/ai-researchers-allege-machine-learning-alchemy
[6] https://www.sciencedaily.com/releases/2019/02/190215110303.htm
[7] https://phys.org/news/2018-09-machine-scientific-discoveries-faster.html
[8] https://www.americanscientist.org/blog/macroscope/people-cause-replication-problems-not-machine-learning
[9] https://www.datanami.com/2019/02/19/machine-learning-for-science-proving-problematic/
[10] https://www.quantamagazine.org/how-artificial-intelligence-is-changing-science-20190311/
[11] https://ml4sci.lbl.gov/
[12] https://blogs.nvidia.com/blog/2019/03/27/how-ai-machine-learning-are-advancing-academic-research/