diff --git a/components/infoPage/infoBox/InfoCredit.tsx b/components/infoPage/infoBox/InfoCredit.tsx
index e149841..fa15260 100644
--- a/components/infoPage/infoBox/InfoCredit.tsx
+++ b/components/infoPage/infoBox/InfoCredit.tsx
@@ -25,7 +25,7 @@ const InfoCredit = () => {
         </div>
         <div>
           <h2 className='font-semibold text-medium text-black'>ClimateGAN Cycle-GAN Image Generator</h2>
-          <p className='font-regular text-medium text-black'>"ClimateGAN: Raising Climate Change Awareness by Generating Images of Floods." Schmidt et al. International Conference on Learning Representations, 2022. <a href="https://openreview.net/forum?id=EZNOb_uNpJk" target="_blank">[link to paper]</a> <a href="/cc-ai/climategan" target="_blank">[link to GitHub repository]</a></p>
+          <p className='font-regular text-medium text-black'>ClimateGAN: Raising Climate Change Awareness by Generating Images of Floods. Schmidt et al. International Conference on Learning Representations, 2022. <a href="https://openreview.net/forum?id=EZNOb_uNpJk" target="_blank">[link to paper]</a> <a href="/cc-ai/climategan" target="_blank">[link to GitHub repository]</a></p>
         </div>
         <div>
           <h2 className='font-semibold text-medium text-black'>Coastal Flooding</h2>
@@ -46,7 +46,7 @@ const InfoCredit = () => {
       </div>
       <div className='flex flex-col gap-[0.625rem] mt-6'>
         <h3 className='font-semibold text-heading text-black'>Methodology & Limitations</h3>
-        <p className='font-regular text-medium text-black'>The flood images featured on this website were generated using the open-source <a href="/cc-ai/climategan" target="_blank" className='underline'>ClimateGAN</a> image generation models. The ClimateGAN model is licensed under GPL-3.0 and is open for public use, promoting transparency and collaboration. The model code, data, and pre-trained weights available in the original ClimateGAN repository were applied to Cylomedia street view images from the geocoder.nyc website to generate the photorealistic images of flooding. In order to generate images with mild, moderate, and major flooding levels, the threshold parameter of the model was set to 0.99, 0.9, and 0.8 respectively. Although these values do not correspond to exact measurements of flooding, we estimate that the mild, moderate, and major flooding levels correspond to the approximate ranges &lt; 0.4 inches, 0.4–12 inches, and 12–24 inches respectively. In a future iteration, we hope to improve the model performance by feeding an initial flood mask generated via the elevation tool on the geocoder.nyc website to the model. Stay tuned for further updates!</p>
+        <p className='font-regular text-medium text-black'>The flood images featured on this website were generated using the open-source <a href="/cc-ai/climategan" target="_blank" className='underl'>ClimateGAN</a> image generation models. The ClimateGAN model is licensed under GPL-3.0 and is open for public use, promoting transparency and collaboration. The model code, data, and pre-trained weights available in the original ClimateGAN repository were applied to Cylomedia street view images from the geocoder.nyc website to generate the photorealistic images of flooding. In order to generate images with mild, moderate, and major flooding levels, the threshold parameter of the model was set to 0.99, 0.9, and 0.8 respectively. Although these values do not correspond to exact measurements of flooding, we estimate that the mild, moderate, and major flooding levels correspond to the approximate ranges &lt; 0.4 inches, 0.4–12 inches, and 12–24 inches respectively. In a future iteration, we hope to improve the model performance by feeding an initial flood mask generated via the elevation tool on the geocoder.nyc website to the model. Stay tuned for further updates!</p>
       </div>
     </div>
   )