The expression you provided is a logistic function:

$f(x) = \frac{1}{1 + e^{-(x - 10)}}$

This is often used in fields like statistics, machine learning, and biology to model "S"-shaped growth curves, probability distributions, or sigmoid functions. The term $e^{-(x - 10)}$ indicates a transformation that shifts the curve horizontally by 10 units to the right.

Would you like a deeper breakdown of its behavior, including graphing or solving for specific values?

Here are some relative questions:

1. How does the logistic function behave as $x \to \infty$ and $x \to -\infty$?
2. How is the point $x = 10$ significant in this function?
3. What is the derivative of this logistic function?
4. How does this function relate to logistic regression in machine learning?
5. How can you solve for $x$ given a specific value of $f(x)$?

Tip: Logistic functions are often used to model growth processes that have a maximum limit, such as population growth or the spread of information.