Article “金森誠之” in Japanese Wikipedia has 12.7 points for quality (as of July 1, 2025). The article contains 7 references and 8 sections. The article also contains templates indicating quality issues, therefore its score was reduced by 0.67 points.
Since the creation of article “金森誠之”, its content was written by 17 registered users of Japanese Wikipedia and edited by 17 registered Wikipedia users in all languages.
The article is cited 10 times in Japanese Wikipedia and cited 10 times in all languages.
The highest Authors Interest rank from 2001:
The highest popularity rank from 2008:
There is 1 language version for this article in the WikiRank database (of the considered 55 Wikipedia language editions).
The quality and popularity assessment was based on Wikipédia dumps from July 1, 2025 (including revision history and pageviews for previous years).
| Best Rank | Japanese: #371129 08.2024 |
Global: #2978481 08.2024 |
| Best Rank | Japanese: #37042 05.2011 |
Global: #815239 05.2011 |
On 16 March 2026 in multilingual Wikipedia, Internet users most often read articles on the following topics: 98th Academy Awards, Michael B. Jordan, Sinners, Jessie Buckley, Paul Thomas Anderson, Sean Penn, One Battle After Another, Amy Madigan, Hamnet, Timothée Chalamet.
In Japanese Wikipedia the most popular articles on that day were: 小泉八雲, 同志社国際中学校・高等学校, 若嶋津六夫, 伊藤大海 (野球), 高橋成美, 井端弘和, 太田裕二, ワールド・ベースボール・クラシック, 高田みづえ, 尾崎将司.
The WikiRank project is intended for automatic relative evaluation of the articles in the various language versions of Wikipedia. At the moment the service allows to compare over 44 million Wikipedia articles in 55 languages. Quality scores of articles are based on Wikipedia dumps from July, 2025. When calculating current popularity and AI of articles data from June 2025 was taken into account. For historical values of popularity and AI WikiRank used data from 2001 to 2025... More information
$$Quality=1/c∑↙{i=1}↖c nm_i-RS=1/5(8.51+2.53+0+25.81+29.75)-0.67$$
where:
The results of the calculations may be slightly different because of rounded values of normalized metrics in formulas
