Revert "Update recore_vector preview/GA status in knn.md" (elastic#1513)

Reverts elastic#1495

A [silly person](https://github.com/leemthompo) thought we already
sanitized the unreleased version in the output, but we don't (yet) so
this shouldn't have merged (yet).

Author: leemthompo

solutions/search/vector/knn.md

@@ -918,11 +918,7 @@ All forms of quantization will result in some accuracy loss and as the quantizat
 * `int4` requires some rescoring for higher accuracy and larger recall scenarios. Generally, oversampling by 1.5x-2x recovers most of the accuracy loss.
 * `bbq` requires rescoring except on exceptionally large indices or models specifically designed for quantization. We have found that between 3x-5x oversampling is generally sufficient. But for fewer dimensions or vectors that do not quantize well, higher oversampling may be required.
 
-#### The `rescore_vector` option
-```{applies_to}
-stack: preview 9.0, ga 9.1
-```
-You can use the `rescore_vector` option to automatically perform reranking. When a rescore `oversample` parameter is specified, the approximate kNN search will:
+You can use the `rescore_vector` [preview] option to automatically perform reranking. When a rescore `oversample` parameter is specified, the approximate kNN search will:
 
 * Retrieve `num_candidates` candidates per shard.
 * From these candidates, the top `k * oversample` candidates per shard will be rescored using the original vectors.