Article "Вибіркове подрібнення" in Ukrainian Wikipedia has 6 points for quality (as of July 1, 2025). The article contains 0 references and 3 sections.
Since the creation of article "Вибіркове подрібнення", its content was written by 4 registered users of Ukrainian Wikipedia and edited by 4 registered Wikipedia users in all languages.
The article is cited 2 times in Ukrainian Wikipedia and cited 2 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 | Ukrainian: #65775 11.2008 |
Global: #4764039 11.2008 |
| Best Rank | Ukrainian: #12109 11.2012 |
Global: #958564 11.2012 |
On 12 August 2025 in multilingual Wikipedia, Internet users most often read articles on the following topics: Cristiano Ronaldo, Wednesday, Georgina Rodríguez, ChatGPT, Weapons, Jenna Ortega, deaths in 2025, Taylor Swift, Miguel Uribe Turbay, 2025–26 UEFA Champions League.
In Ukrainian Wikipedia the most popular articles on that day were: Забарний Ілля Борисович, Аляска, Анкоридж (Аляска), Макс Корж, Венздей (2-й сезон), 1-й корпус НГУ «Азов», День молоді (Україна), Волинська трагедія, Кріштіану Роналду, Україна.
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
$$Quality=1/c∑↙{i=1}↖c nm_i-RS=1/5(5.9+0+11.11+13.04+0)$$
where:
The results of the calculations may be slightly different because of rounded values of normalized metrics in formulas
