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ChatGPT Generated Content and Similarity Index in Chemistry & Allied Sciences
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2023
Jahr
Abstract
The main objective of this study is to verify similarity index of ChatGPT generated content in the field of chemistry and its allied subjects. To complete this study twenty sub subjects of chemistry based on controlled vocabulary tools such as Dewey Decimal Classification (DDC) system, Sears List of Subject Headings and Library of Congress Subject Headings (LCSH) have considered for sample, followed by content generation and similarity check using iThenticate, Urkund and Turnitin. The percentage of matching paragraphs is relatively low as the three plagiarism software shows 12%, 1% and 5% respectively.
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