  We performed a citation analysis on the Web of Science publications
consisting of more than 63 million articles and 1.45 billion citations on 254
subjects from 1981 to 2020. We proposed the Article's Scientific Prestige (ASP)
metric and compared this metric to number of citations (#Cit) and journal grade
in measuring the scientific impact of individual articles in the large-scale
hierarchical and multi-disciplined citation network. In contrast to #Cit, ASP,
that is computed based on the eigenvector centrality, considers both direct and
indirect citations, and provides steady-state evaluation cross different
disciplines. We found that ASP and #Cit are not aligned for most articles, with
a growing mismatch amongst the less cited articles. While both metrics are
reliable for evaluating the prestige of articles such as Nobel Prize winning
articles, ASP tends to provide more persuasive rankings than #Cit when the
articles are not highly cited. The journal grade, that is eventually determined
by a few highly cited articles, is unable to properly reflect the scientific
impact of individual articles. The number of references and coauthors are less
relevant to scientific impact, but subjects do make a difference.
