diff --git a/src/test/java/org/opensearch/neuralsearch/processor/combination/GeometricMeanScoreCombinationTechniqueTests.java b/src/test/java/org/opensearch/neuralsearch/processor/combination/GeometricMeanScoreCombinationTechniqueTests.java
index 4f6c6f0cf..fe0d962ca 100644
--- a/src/test/java/org/opensearch/neuralsearch/processor/combination/GeometricMeanScoreCombinationTechniqueTests.java
+++ b/src/test/java/org/opensearch/neuralsearch/processor/combination/GeometricMeanScoreCombinationTechniqueTests.java
@@ -76,17 +76,23 @@ public void testRandomValues_whenNotAllScoresAndWeightsPresent_thenCorrectScores
         testRandomValues_whenNotAllScoresAndWeightsPresent_thenCorrectScores(technique, weights);
     }
 
+    /**
+     * Verify score correctness by using alternative formula for geometric mean as n-th root of product of weighted scores,
+     * more details in here https://en.wikipedia.org/wiki/Weighted_geometric_mean
+     */
     private float geometricMean(List<Float> scores, List<Double> weights) {
-        assertEquals(scores.size(), weights.size());
-        float sumOfWeights = 0;
-        float weightedSumOfLn = 0;
-        for (int i = 0; i < scores.size(); i++) {
-            float score = scores.get(i), weight = weights.get(i).floatValue();
-            if (score > 0) {
-                sumOfWeights += weight;
-                weightedSumOfLn += weight * Math.log(score);
+        float product = 1.0f;
+        float sumOfWeights = 0.0f;
+        for (int indexOfSubQuery = 0; indexOfSubQuery < scores.size(); indexOfSubQuery++) {
+            float score = scores.get(indexOfSubQuery);
+            if (score <= 0) {
+                // scores 0.0 need to be skipped, ln() of 0 is not defined
+                continue;
             }
+            float weight = weights.get(indexOfSubQuery).floatValue();
+            product *= Math.pow(score, weight);
+            sumOfWeights += weight;
         }
-        return sumOfWeights == 0 ? 0f : (float) Math.exp(weightedSumOfLn / sumOfWeights);
+        return sumOfWeights == 0 ? 0f : (float) Math.pow(product, (float) 1 / sumOfWeights);
     }
 }