Testing the Reliability of ChatGPT in Providing Spectral Information

ChatGPT has emerged as a tool for predicting Hydrogen-1 Nuclear Magnetic Resonance (1HNMR), Infrared (IR), and Mass Spectrometry (MS) spectra. In order to rely on ChatGPT as a tool, a proof of concept for its application was essential. Having the ChatGPT outputs be validated by experimental data and databases (SDBS) has proven valuable for future uses. By inference, ChatGPT spectra output can be used to design problems without interference of copyright infringement of existing databases.

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Publication Details

Journal
Advances in Peer-Led Learning
Published
2024-12-20
DOI
https://doi.org/10.54935/apll2024-01-07-69
Primary Topic
COVID-19 diagnosis using AI
Type
article
Field-Weighted Citation Impact
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article

Testing the Reliability of ChatGPT in Providing Spectral Information

Eduardo Santos Sánchez, A. Fraiman, S. Delgado, Paola Barron et al.
1 links
Advances in Peer-Led Learning
COVID-19 diagnosis using AI
article

Testing the Reliability of ChatGPT in Providing Spectral Information

Eduardo Santos Sánchez, A. Fraiman, S. Delgado, Paola Barron, Brooke Dorsey
article en

Abstract

ChatGPT has emerged as a tool for predicting Hydrogen-1 Nuclear Magnetic Resonance (1HNMR), Infrared (IR), and Mass Spectrometry (MS) spectra. In order to rely on ChatGPT as a tool, a proof of concept for its application was essential. Having the ChatGPT outputs be validated by experimental data and databases (SDBS) has proven valuable for future uses. By inference, ChatGPT spectra output can be used to design problems without interference of copyright infringement of existing databases.

Advances in Peer-Led Learning(4)
Northeastern Illinois University (US)
Openalex Percentile: Top 57%
COVID-19 diagnosis using AI
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