Which of the following is true according to Alex Burnap and co$-$authors in their paper titled, When crowdsourcing fails?

Group of answer choices

$($A$)$ A Bayesian network model for crowd consensus aims to identify experts such that their contributions may be given more weight.

$($B$)$ Finding experts within the crowd is a solved problem.

$($C$)$ Workers in crowd sourcing systems are likely to give random evaluations.

$($D$)$ It is challenging to distinguish the cluster of experts from the cluster of those workers that are consistently wrong.

$($E$)$ Crowd sourced evaluation can fail due to expertise distribution of the crowd.