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arXivProfiler – An author's credibility viewer for arXiv
Hacker NewsarXivProfiler – An author's credibility viewer for arXiv
When reading papers recently uploaded to arxiv, it is important to approximate the reliability of the paper. The easiest method to filter papers is to check the number of citations of the authors. With this application, you can account for the total number of citations (= credibility of a paper) in an instant from the arxiv link. I hope you like it. Thank you.
Share cardActual performance
2points
Did not reach leaderboard
Launch Intel predictions
Analyze your own launch →Hacker NewsStrong engagement from HN community · Strong signals: io · Missing: https docs, excited, just released52%52% predicted probability of success on Hacker News, based on ML models trained on real launch data.
nativeThis product was originally launched on this platform.
TrustMRRFits verified-revenue profile · Missing: mobile apps, ios, personal51%51% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
Product HuntUnlikely to reach the leaderboard · Missing: mac, agents, macos47%47% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
BetaListMay not resonate with beta-testers · Missing: web3, chat, crypto28%28% predicted probability of success on BetaList, based on ML models trained on real launch data.
AppSumoMay struggle as an AppSumo deal · Missing: plus, platform, intuitive22%22% predicted probability of success on AppSumo, based on ML models trained on real launch data.
Indie HackersIH features products with proven revenue · Missing: supports, reddit linkedin, podcasting21%21% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.
Acquire.comPre-revenue stage for this audience · Missing: arr, mrr, revenue17%17% predicted probability of success on Acquire.com, based on ML models trained on real launch data.
Incorrect prediction on native model
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