I don’t think a high replication rate necessarily implies the experiments were boring. Suppose you do 10 experiments, but they’re all speculative and unlikely to be true: let’s say only one of them is looking at a true effect, BUT your sample sizes are enormous and you have a low significance cutoff. So you detect the one effect and get 9 nulls on the others. When people try to replicate them, they have a 100% success rate on both the positive and the negative results.
The fraction of attempts that will fail due to random chance depends on the power, and replicators tend to go for very high levels of power, so typically you’d have about 5% false negatives or so in the replications.
Did evolution need to understand information encoding in the brain before it achieved full GI?