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add availability to oversample value of 0 (elastic#131707)
(cherry picked from commit 4dd124b)
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docs/reference/elasticsearch/mapping-reference/dense-vector.md

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@@ -277,7 +277,10 @@ $$$dense-vector-index-options$$$
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: (Optional, object) An optional section that configures automatic vector rescoring on knn queries for the given field. Only applicable to quantized index types.
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:::::{dropdown} Properties of rescore_vector
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`oversample`
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: (required, float) The amount to oversample the search results by. This value should be greater than `1.0` and less than `10.0` or exactly `0` to indicate no oversampling & rescoring should occur. The higher the value, the more vectors will be gathered and rescored with the raw values per shard.
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: (required, float) The amount to oversample the search results by. This value should be one of the following:
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* Greater than `1.0` and less than `10.0`
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* Exactly `0` to indicate no oversampling and rescoring should occur {applies_to}`stack: ga 9.1`
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: The higher the value, the more vectors will be gathered and rescored with the raw values per shard.
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: In case a knn query specifies a `rescore_vector` parameter, the query `rescore_vector` parameter will be used instead.
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: See [oversampling and rescoring quantized vectors](docs-content://solutions/search/vector/knn.md#dense-vector-knn-search-rescoring) for details.
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docs/reference/query-languages/query-dsl/query-dsl-knn-query.md

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@@ -113,7 +113,9 @@ Rescoring only makes sense for quantized vectors; when [quantization](/reference
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* Retrieve `num_candidates` candidates per shard.
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* From these candidates, the top `k * oversample` candidates per shard will be rescored using the original vectors.
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* The top `k` rescored candidates will be returned.
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Must be >= 1f to indicate oversample factor, or exactly `0` to indicate that no oversampling and rescoring should occur.
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Must be one of the following values:
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* \>= 1f to indicate the oversample factor
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* Exactly `0` to indicate that no oversampling and rescoring should occur. {applies_to}`stack: ga 9.1`
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See [oversampling and rescoring quantized vectors](docs-content://solutions/search/vector/knn.md#dense-vector-knn-search-rescoring) for details.

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