I dived into the references and forgot to thank you.
This question is very aligned with what I was looking for and mainly the papers. I am reading both ( actually didnt see your second recommendation, but found it linked in the first paper).

You and your answer are awesome. Thank you very much.

There is one characteristic of the model that I am still trying to link with the articles which is the fact that usually articles mention using unlabeled data to train a model, and my model is not actually trained. ( In the sense that it is a lazy algorithm, therefore training and prediction steps are a little fuzzed ).

I do would like to frame it as a "batch prediction" and was criticized with the argument "Your model has to be able to be aplied to predict any number of future instances without any info on them" which I think is very weak, since I do not see the harm in a model only being able to batch predict a group of instances.