Rodrigo
Torres

The lexical half alone misses eleven of twenty-six, and they are the questions that share no word with their passage: whether he builds alone, whether he has broken production, what salary he is after. That is precisely what a vector index exists to answer.

Fusion recovers a question neither half finds on its own, which is the evidence that fusing is not decoration: two weak signals in different lists add up to a position neither reached alone.

It pays for that. The fusion's MRR sits below the vector half's: it puts the answer inside the top four more often and leaves it slightly lower within those four. With four passages going to the model that costs little; with one result on screen it would cost a great deal.

In English the fusion comes out below the vector half alone, 0.769 against 0.846, losing all three questions where they disagree. At n = 26 the sign test gives p = 0.25, which does not separate that from chance. Switching configuration per language on that evidence would be fitting the system to the gold set, so both run the same one.

The Wilson interval is the part that cannot be skipped. A recall of 0.923 over 26 cases is 0.923 [0.76, 0.98]: the system could be at 0.76 and this gold set would not know. Twenty-six cases are a starting point, not an answer.

A real defect came out of this. The two lists entered the fusion at different depths: the lexical one whole, the vector one cut at 12. BM25 keeps every passage scoring above zero, a median of 31 out of 39, so a passage ranked 30th still collected a vote that no comparable vector match could answer. Cutting both to the same depth took Spanish recall from 0.885 to 0.923. The correction is justified by the argument; the figure only says what it had been costing.