How would you tackle prioritized learning? When I research spaced repetition topics, the algorithms are normally not well suited to reviewing something before than its turn...
1. Let's assume: The flash card isn't new. You last review was 100 days ago.
2. It is due in 3 days but you have some extra time today! You have only 10 cards to review but but have some extra time right now and you're are gone for the weekend.
3. It shouldn't matter if you review the flash card today already even though it's only due in 3 days. If it ends up being 100 or 103 days... It doesn't matter. It's all just a probabilistic model anyways with much larger errors.
4. So in premium: After you've reviewed your most pressing/recently-learnt ones you can keep going and pre-learn your old ones.
There is a few more ideas I have but this is basically it.