Based on the results of running the function on different words, here is a preliminary description of the function implemented in `function.py`:

[DESCRIPTION]: The function appears to assign a value between 0 and 1 to words, indicating the degree of association with a specific concept. The function seems to be selective for multiple concepts rather than a single one. The degree of association varies for different words, with values closer to 1 indicating a stronger association with the concept(s). 

Here are the associations for the given set of words:
- "rhythm" - The word has a low association value, suggesting a weak association with the concept(s).
- "ocean" - The word has a moderately low association value, suggesting a moderate association with the concept(s).
- "Empire State Building" - The word has a high association value, indicating a strong association with the concept(s).
- "deposit" - The word has a high association value, indicating a strong association with the concept(s).
- "Pulp Fiction" - The word has a moderately low association value, suggesting a moderate association with the concept(s).
- "language" - The word has a moderately low association value, suggesting a moderate association with the concept(s).
- "series" - The word has a moderately low association value, suggesting a moderate association with the concept(s).
- "deadly" - The word has a moderately low association value, suggesting a moderate association with the concept(s).
- "Amtrak" - The word has a moderately high association value, suggesting a moderate to strong association with the concept(s).
- "Walter White" - The word has a moderately low association value, suggesting a moderate association with the concept(s).

It is important to note that without additional information or a larger number of tests, it may be difficult to precisely determine the underlying concept(s) that the function is selective for.