Regarding the frequency used for scoring sloppy phrase queries.

### Description

I've been using Lucene (through OpenSearch) for querying and scoring human-written documents (!= logs). I often use sloppy phrase queries to handle languages variations which express similar meaning.

For example, one of my query contained `"frauduleus faillissement"~3` (in Dutch. This is equivalent to "fraudulent bankruptcy" in English). Thanks to the sloppy match, the following two sentences are correctly matched by that query:
1. Dit faillissement is frauduleus (This bankruptcy is fraudulent)
2. Dit is een frauduleus faillissement (This is a fraudulent bankruptcy)

While the two sentences are very similar in meaning, the way they are scored by the `SloppyPhraseScorer` is very different. According to the following lines the sentences will have respectively a frequency of `0.25` and `1`, leading to a large difference in the resulting relevance score.
https://github.com/apache/lucene/blob/3ce9ba9fd51a9b4e7228d81e19acbdb8b18f4e12/lucene/core/src/java/org/apache/lucene/search/SloppyPhraseMatcher.java#L166-L169,

While I understand the intent of `sloppyWeight()` to penalize sloppy matches that are different from the exact match, I feel that the penalty is way too strong. As a user, I deliberately make the choice to look for sloppy phrase matches and I wouldn't expect that such a strong penalty would apply. For that particular example, I would obtain a more accurate scoring by using multiple exact phrase queries.

Browsing the history of `SloppyPhraseScorer`, I see that this scoring approach has been in place for years and I did not find any issue discussing that implementation. Even though my use case might be niche, I believe a revision of that scoring method could greatly benefit applications on human-written texts.

Start with the linked SloppyPhraseMatcher.java lines around sloppyWeight(), then read the surrounding SloppyPhraseScorer implementation and its history. Reproduce the two Dutch sentence examples and compare their frequencies; done would require an agreed revision to sloppy phrase scoring, which the issue does not yet specify.

Written by the indexing model from the issue text.