Help:New filters for edit review/pl

Nowi filtry dla Edit Review to funkcja eksperymentalna dodająca nowe filtrowanie i narzędzia dla stron Specjalna:Ostatnie_zmiany i Specjalna:Zmiany_w_linkowanych (początkowo).

These improvements help reviewers to better target their efforts and be more efficient. They also have the potential to particularly benefit new contributors, who require a more supportive edit-review process, according to research.

Aby zapoznać się z tym narzędziem, odwiedź szybki przewodnik. To learn how to use the advanced functions provided, explore the pages described below.

Wprowadzanie tej nowej funkcji rozpocznie się w marcu 2017. Początkowo “Nowe filtry do patrolowania edycji” nie będą dostępne na urządzeniach mobilnych.

Funkcje

 * This page explains how the improved filtering interface works and how to get the most out of the new tools.
 * This page explains how the improved filtering interface works and how to get the most out of the new tools.


 * User-defined Highlighting tools let you use color to emphasize the edits that interest you most. The functions and techniques described on this page will help you to make your Recent Changes results more meaningful.
 * User-defined Highlighting tools let you use color to emphasize the edits that interest you most. The functions and techniques described on this page will help you to make your Recent Changes results more meaningful.


 * "New filters for edit review" introduces two filter groups—Contribution Quality and User Intent—that are powered by machine learning and work differently from other filters. They offer probabilistic predictions about, respectively, whether or not edits are likely to contain problems and whether the user who made them was acting in good faith. Knowing a bit about how these unique tools work will help you use them more effectively.
 * "New filters for edit review" introduces two filter groups—Contribution Quality and User Intent—that are powered by machine learning and work differently from other filters. They offer probabilistic predictions about, respectively, whether or not edits are likely to contain problems and whether the user who made them was acting in good faith. Knowing a bit about how these unique tools work will help you use them more effectively.