As mentioned in the comments, I would suggest what’s called the ‘compromise solution’ to anyone with a similar problem who is more concerned with not having to set weights than with making one criterion more heavily weighted than the others.
Basically, you consider each of your criterion as a coordinate (after normalization, of course). Based on your judgement, you choose the absolute optimal point, e.g. in this case, the highest rank author, the newest article, etc. Once you choose the optimal solution, each other ‘solution’ is rated based on its distance from that optimal. A sample formula would be the inverse of the Euclidean distance for each article’s score: S = 1/(sqrt((rank – rank_ideal)^2 + (age – age_ideal)^2 + … + (xn – xn_ideal)^2)).
This treats all criteria as equal, so keep that in mind.