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

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

In Copyright. URI: http://rightsstatements.org/vocab/InC/1.0/ This Item is protected by copyright and/or related rights. You are free to use this Item in any way that is permitted by the copyright and related rights legislation that applies to your use. For other uses you need to obtain permission from the rights-holder(s).

Persistent Identifier

https://archives.pdx.edu/ds/psu/43657

Available for download on Sunday, June 14, 2026

Share

COinS