Definition: You are given a question or fill-in-the-blank question, two answer options (Option1 and Option2) and an Explanation. Your task is to find the correct answer (return the string of the correct option, not option1/2) for the given question from the given options and using explanation.

Positive Example 1 -
Input: Question: The government of Canada is considering implementing less carbon taxes across the country. If these taxes were implemented, the amount of carbon dioxide emissions in the country would be expected to 
 Option1: fall 
 Option2: rise 
 Explanation: The carbon taxes encourage people to use less fossil fuel, which reduces carbon dioxide emissions.
Output: rise

Positive Example 2 -
Input: Question: Shampoos with high ph are 
 Option1: less acidic 
 Option2: more 
 Explanation: Lower pH numbers are more acidic and higher numbers are less acidic (also called more alkaline).
Output: more

Negative Example 1 -
Input: Question: The government of Canada is considering implementing less carbon taxes across the country. If these taxes were implemented, the amount of carbon dioxide emissions in the country would be expected to 
 Option1: fall 
 Option2: rise 
 Explanation: The carbon taxes encourage people to use less fossil fuel, which reduces carbon dioxide emissions.
Output: fall

Negative Example 2 -
Input: Question: Shampoos with high ph are 
 Option1: less acidic 
 Option2: more 
 Explanation: Lower pH numbers are more acidic and higher numbers are less acidic (also called more alkaline).
Output: less acidic

Now complete the following example -
Input: Question: Stephanie had designed a machine learning algorithm to help predict earthquakes. Today, her new supercomputer arrived and she will soon run the algorithm on the less powerful computer. The new computer will _____ the accuracy of the model's predictions. 
 Option1: increase 
 Option2: decrease 
 Explanation: But the more computing power that goes into the model and the care with which the scientists construct the model can increase the chances that a model will be accurate.
Output: 


Answer: decrease