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In this paper, we compared the author\u2019s perception of a manuscript\u2019s quality with the manuscript\u2019s actual impact. In addition, we analyzed the uncertainty of the author\u2019s perception of the manuscript\u2019s quality. From there, we defined \u2018partition\u2019 as the author\u2019s ability to perceive the actual quality. We did this by launching a website for the use of the scientific community. This webpage provided a tool to help improve an investigator\u2019s skill in understanding and recognizing the quality of a manuscript so as to help researchers improve and maximize their works\u2019 potential impact. We carried out the experiment with 106 experienced users who tested our webpage. We found that the Abstract, the Title, and the Keywords were enough to perform a substantially decent evaluation of a manuscript. Most of the researchers were able to determine the quality of a paper in less than a minute from this small amount of information.<\/jats:p>","DOI":"10.1007\/s11042-023-14451-9","type":"journal-article","created":{"date-parts":[[2023,2,27]],"date-time":"2023-02-27T14:03:01Z","timestamp":1677506581000},"page":"23075-23090","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":11,"title":["The relevance of title, abstract, and keywords for scientific paper quality and potential impact"],"prefix":"10.1007","volume":"82","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-6334-3786","authenticated-orcid":false,"given":"Jorge","family":"Chamorro-Padial","sequence":"first","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7886-9329","authenticated-orcid":false,"given":"Rosa","family":"Rodr\u00edguez-S\u00e1nchez","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2023,2,27]]},"reference":[{"issue":"3","key":"14451_CR1","doi-asserted-by":"publisher","first-page":"73","DOI":"10.3390\/info8030073","volume":"8","author":"X Bai","year":"2017","unstructured":"Bai X, Liu H, Zhang F, Ning Z, Kong X, Lee I, Xia F (2017) An overview on evaluating and predicting scholarly article impact. 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