Decisional DNA gathers explicit experiential knowledge based on formal decision events and uses this knowledge to support decision-making processes.
Decisional DNA, as a knowledge representation structure, offers great possibilities on gathering explicit knowledge of formal decision events as well as a tool for decision making processes.
Decision analytic techniques use formal specifications of utility for the four fundamental decision events: true positives, false positives, true negatives, and false negatives.
However, the possible randomness (if no bias is assumed) in perceiving the other agents' peer-appreciations is in the model of similar type, and with similar effects, as randomness described by (pi _mathrm{o}), i.e. adding noise in individual decision events.
It is also shown that, in the regime studied, the decision events become Poissonian in the limit of vanishing noise, leading to an exponential distribution of decision times.
Each branch of the decision tree represents one of the possible sequences of chance and decision events that could occur, which is in turn associated with a specific consequence that is valued based on its desirability.
If James had ended his hour-long infomercial in 2010 by telling the host Jim Gray that he was staying in Cleveland, the whole "Decision" event would be remembered very differently today, as a joyful, if self-important, expression of loyalty.
Star and Griesemer claim that the creation and management of boundary objects is a crucial process in the development and maintenance of coherence between different worlds which intersect around a specific decision event.
But a month after the "Decision" event, James is back at it, and he's managed to paint himself as even more of a petulant juvenile than he was before.
An outstanding question is whether organelle dynamics and/or recently discovered subcellular variations of protein levels responsible for both MOMP sensitivity and crosstalk between apoptosis and mitophagy can influence the cellular apoptosis decision event.
