Hello! I was browsing the [Azure Cognitive Search Vector Search example](https://github.com/retkowsky/Azure-OpenAI-demos/blob/main/Azure%20Cognitive%20Search%20Vector%20Search%20Code%20Sample%20with%20Azure%20OpenAI/Azure%20Cognitive%20Search%20Vector%20Search%20Code%20Sample%20with%20Azure%20OpenAI.ipynb), and I noticed a shift in the range of score values between vector search with one vector: score~0.8 <img width="299" alt="image" src="https://github.com/retkowsky/Azure-OpenAI-demos/assets/42930988/fa76dc40-2f0c-4b8f-8239-61a4539634ab"> and when involving multiple vectors (cross-field or multi-vector): score~0.03 <img width="312" alt="image" src="https://github.com/retkowsky/Azure-OpenAI-demos/assets/42930988/6801ed2a-2287-43ae-a9d1-6a8c64437af7"> Do you have any explanation or resources concerning the score value shift? In my use-case, I am thinking about leveraging score values, for instance filtering based on some score value. To do so, I need to grasp the Thanks for your help!