First Advisor
Mark Woods
Date of Award
Spring 6-14-2024
Document Type
Thesis
Degree Name
Bachelor of Science (B.S.) in Chemistry and University Honors
Department
Chemistry
Language
English
Subjects
Publication bias, generative AI, chelate stability, NSF, GDD
DOI
10.15760/honors.1623
Abstract
Throughout this study it became apparent that Generative artificial intelligence lacks the ability to identify publication bias and is not always able to grasp the central message, despite several attempts and methods seeking to correct such publication bias. Due to the training of AI which consists of consuming information from the internet and providing information by predictive algorithm methods the presence of bias was expected. The goal then was to investigate if generative AI, using ChatGPT as our tool, could correct its outputs based on inputs provided. The subject matter focused on research conducted in our laboratory, gadolinium based contrast agents (GBCAs), which there is significant misconception and disagreement in regard to safety concerns.
Rights
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Persistent Identifier
https://archives.pdx.edu/ds/psu/43657
Recommended Citation
Rodriguez Rodriguez, Esperanza Y., "Publication Bias in the Output of Generative AI" (2024). University Honors Theses. Paper 1591.
https://doi.org/10.15760/honors.1623