How to Calculate Search Scores and Rankings for Hybrid Searches

Hi team,
I am wondering how search scores and rankings are calculated for hybrid searches.
I did a search with keyword search(top=10) and vector search(vector.k=10) and got the following ranking.
RRFscore(d) = Σ (1 / (_k_ + rank_d_i)) with constant _k_ = 59.

**1, Simple Vector Search Result**
| FileName | Vector-Rank | Vector-RRF |
| ------------- | ------------- |------------- |
| A.txt | 2 | 1/(_k_+2)=0.016393443 |
| B.txt | 1 | 1/(_k_+1)=0.016666667 |
| C.txt | 3 | 1/(_k_+3)=0.016129032 |

**2, Simple Keyword Search Result**
| FileName | Keyword-Rank | Keyword-RRF |
| ------------- | ------------- |------------- |
| A.txt | 8 | 1/(_k_+8)=0.014925373 |
| B.txt | 10 | 1/(_k_+10)=0.014492754 |
| C.txt | None | 1/(_k_+?)=None |

**3, Σ RRF**
| FileName | calclated-RRF | displayed-RRF |
| ------------- | ------------- |------------- |
| A.txt | 1/(_k_+2)+1/(_k_+8)=0.031318816 | ≈0.03131881356239319 |
| B.txt | 1/(_k_+1)+1/(_k_+10)=0.031159420 | ≈0.031159421429038048 |
| C.txt | 1/(_k_+3)=0.016129032 | **≠0.029286926612257957** |

**Question 1.**
[The docs](https://github.com/Azure/cognitive-search-vector-pr/blob/main/docs/vector-search-overview.md#reciprocal-rank-fusion) describe _k_= like 60, but my calculation seems to be 59, how much is it actually?

**Question 2.**
"C.txt" was not found in the Simple Keyword Search (top=10) results. How is the RRF calculated in this case? My guess is that internally a larger value than I specified in my top query is specified and its ranking is calculated.

Start with the linked Reciprocal Rank Fusion section in docs/vector-search-overview.md and compare its description with the reported keyword and vector rankings. Determine the actual constant and how documents missing from one result set are scored; done means the documentation answers both questions accurately, with the example reconciled.

Written by the indexing model from the issue text.