Impact Factor Finder
Show IF, JCR quartiles, OA status, Top 2% insight, O-index, Scholar profile infographics, and smart author-position highlighting.
Scan Google Scholar Profile and pull latest SJR (SCImago Journal Rank) Categories and metrics for academic publications.
按已采集快照查看用户数变化。
展示最近 7 日窗口内已采集的评分快照,辅助判断近期评分是否稳定。
同口径展示 1 天、7 天、30 天的绝对增长与增长率。
查看发布时间、版本、支持语言、最近更新和抓取时间。
查看插件说明、主要功能和适用场景。
Unlock Comprehensive SJR Journal Ranking information on Google Scholar
"SJR Insights for Google Scholar Profiles" is a powerful Chrome extension designed for academics & researchers who frequently use Google Scholar Profile. This tool empowers you to seamlessly integrate Scimago Journal Rank (SJR) data directly into your Google Scholar Profile, allowing for quick review of your publications’ journal quality and impact.
By uploading your own SJR dataset (you can download this here https://www.scimagojr.com/journalrank.php ), this extension transforms how you interact with journal information on Google Scholar citation pages. Instantly identify journal quartiles, precise category ranks, and percentiles at a glance, or use the robust popup interface to search for specific ISSNs and export curated results.
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Key Features:
• Seamless Google Scholar Integration: Once your SJR data is loaded, the extension automatically displays clear "SJR Quartile" badges next to journal titles on Google Scholar citation profiles.
查看最近评论和评分分布。
商店综合星级:5.0。下方星级分布只统计已同步评论正文;如果某个插件只有公开分数、没有真实评论正文,这里可能为空。
查看 Chrome 商店详情页中的相关产品。
Show IF, JCR quartiles, OA status, Top 2% insight, O-index, Scholar profile infographics, and smart author-position highlighting.
Fetches Google Scholar total citations and displays it on the extension badge.
Display journal impact factors and citation info on LitSense and Google Scholar search results. Powered by LitSource.
Highlights the name of the Google Scholar profile in all publications.
Automatically Discover Quartile Information to Google Scholar page. You can search more data in detail manually.
Calculates author self-citation rates on Google Scholar using DBLP, OpenCitation, and OpenAlex data.