Problem A
Nonsense

The effect of the popularity of B-trees.

Catastrophy! Your esteemed scientific journal has been exposed for accepting a paper that can best be described as well-formatted nonsense. It turns out that it was generated by a particular program. Although you don’t know much about it, you can be certain that it is quite old, given the poor quality of the papers it produces.

To assess the damage, you want to write a program to estimate how many existing publications have been produced by said program. It is of course very important to not accidentally report a human paper as being written by the program.

You have already completed the arduous task of converting the papers to plain text. All that is left is to write the program.

Input

Input consists of a single line of at most $3 \cdot 10^5$ characters, the contents of a paper. Look at attachments for examples.

Output

Print “Fake” if you think the paper is fake, otherwise “Real”.

Scoring

Your solution will be tested on multiple test cases different from the ones given. The secret tests are guaranteed to be comparable to the given examples. The total score is calculated using the following formula:
$\text{Score} = 100 \cdot \text{truePositive} \cdot \text{trueNegative}^{2.5}$.
where $\text{truePositive}$ is the percentage of fake papers you correctly identify,
and $\text{trueNegative}$ is the percentage of real papers you correctly identify.

In particular, if you always answer correctly, you will get 100 points. The exponent means that it is very important to not incorrectly classify real papers as fake.

At the end of the competition, all solutions will be retested on the remaining 70% of the data. Your final score at the end of the competition will only be based on the remaining 70% of the data; the 30% tested during the competition will have no effect. It is guaranteed that the 30% tested during the competition were chosen uniformly at random and are entirely disjoint from the 70% tested at the end. Therefore, the results on the 30% tested during the competition should be seen as a strong indicator of how well your solution performs. At the same time, it is detrimental to overfit your solution to the test data.