From 3199f577136b5466cfb751c0f15c99024c624d95 Mon Sep 17 00:00:00 2001
From: shainaraskas <58563081+shainaraskas@users.noreply.github.com>
Date: Fri, 25 Jul 2025 09:57:24 -0700
Subject: [PATCH] add availability information for rescore_vector (#131710)

(cherry picked from commit 9c23d7386045bcbf9e52f2e153ff41a1ed8fb68b)
---
 docs/reference/elasticsearch/mapping-reference/dense-vector.md  | 2 +-
 .../elasticsearch/rest-apis/retrievers/knn-retriever.md         | 2 +-
 docs/reference/query-languages/query-dsl/query-dsl-knn-query.md | 2 +-
 3 files changed, 3 insertions(+), 3 deletions(-)

diff --git a/docs/reference/elasticsearch/mapping-reference/dense-vector.md b/docs/reference/elasticsearch/mapping-reference/dense-vector.md
index 7f3a701bde3f8..1acc9b2462031 100644
--- a/docs/reference/elasticsearch/mapping-reference/dense-vector.md
+++ b/docs/reference/elasticsearch/mapping-reference/dense-vector.md
@@ -273,7 +273,7 @@ $$$dense-vector-index-options$$$
 :   (Optional, float) Only applicable to `int8_hnsw`, `int4_hnsw`, `int8_flat`, and `int4_flat` index types. The confidence interval to use when quantizing the vectors. Can be any value between and including `0.90` and `1.0` or exactly `0`. When the value is `0`, this indicates that dynamic quantiles should be calculated for optimized quantization. When between `0.90` and `1.0`, this value restricts the values used when calculating the quantization thresholds. For example, a value of `0.95` will only use the middle 95% of the values when calculating the quantization thresholds (e.g. the highest and lowest 2.5% of values will be ignored). Defaults to `1/(dims + 1)` for `int8` quantized vectors and `0` for `int4` for dynamic quantile calculation.
 
 
-`rescore_vector`
+`rescore_vector` {applies_to}`stack: preview 9.0, ga 9.1`
 :   (Optional, object) An optional section that configures automatic vector rescoring on knn queries for the given field. Only applicable to quantized index types.
 :::::{dropdown} Properties of rescore_vector
 `oversample`
diff --git a/docs/reference/elasticsearch/rest-apis/retrievers/knn-retriever.md b/docs/reference/elasticsearch/rest-apis/retrievers/knn-retriever.md
index 817f4d3fab681..12da522214383 100644
--- a/docs/reference/elasticsearch/rest-apis/retrievers/knn-retriever.md
+++ b/docs/reference/elasticsearch/rest-apis/retrievers/knn-retriever.md
@@ -60,7 +60,7 @@ A kNN retriever returns top documents from a [k-nearest neighbor search (kNN)](d
     Read more here: [knn similarity search](docs-content://solutions/search/vector/knn.md#knn-similarity-search)
 
 
-`rescore_vector`
+`rescore_vector` {applies_to}`stack: preview 9.0, ga 9.1`
 :   (Optional, object) Apply oversampling and rescoring to quantized vectors.
 
 ::::{note}
diff --git a/docs/reference/query-languages/query-dsl/query-dsl-knn-query.md b/docs/reference/query-languages/query-dsl/query-dsl-knn-query.md
index ab2dd232eaf50..dee7fc8d47b88 100644
--- a/docs/reference/query-languages/query-dsl/query-dsl-knn-query.md
+++ b/docs/reference/query-languages/query-dsl/query-dsl-knn-query.md
@@ -97,7 +97,7 @@ The filter is a pre-filter, meaning that it is applied **during** the approximat
 :   (Optional, float) The minimum similarity required for a document to be considered a match. The similarity value calculated relates to the raw [`similarity`](/reference/elasticsearch/mapping-reference/dense-vector.md#dense-vector-similarity) used. Not the document score. The matched documents are then scored according to [`similarity`](/reference/elasticsearch/mapping-reference/dense-vector.md#dense-vector-similarity) and the provided `boost` is applied.
 
 
-`rescore_vector`
+`rescore_vector` {applies_to}`stack: preview 9.0, ga 9.1`
 :   (Optional, object) Apply oversampling and rescoring to quantized vectors.
 
 ::::{note}