Investigating the diversification of Magnoliidae is of primary importance to provide guidance for future hypotheses on the drivers of diversification of flowering plants as a whole.
Under conditions of high complexity, it combines existing know-how and knowledge with future hypotheses – in the mode of the present: if what lies in front of us no longer offers criteria for selection because it has become so extensive, confusing, insecure and even uncertain, all that remains for us is to contemplate selection criteria more intensively that are anchored in the here and now.
We recognize that down-regulation of a broad spectrum of genes may reflect a non-specific toxicity rather than mechanistic regulation of specific genes, a subject of future hypotheses.
However, it was a useful concept from which to synthesize independent lines of evidence and can serve as a basis for future hypothesis testing of the two scenarios.
Finally, the OFS can be readily adapted to accommodate a variety of future hypotheses and experiments.
In this section, we describe a method in which the said information is applied proactively, that is, in a manner whereby previously evaluated solutions direct the choice of future hypotheses.
Our model can be extended as a general analytical approach for future hypothesis testing of bark beetle fungal associations.
To explore this methodology as a way of generating future hypotheses concerning obesity-related factors, we specifically focused on community-level factors previously correlated with obesity, such as access to nutritious food and physical activity, as well as income, population size and education.
This study also adds to the growing body of literature on strain geographic, clinical, and epidemiologic diversity and provides vital insights for generation of future hypothesis-driven studies of strain virulence and transmissibility.
Overall, we do not only percolate probabilities of active hypotheses upward, but also adjust the prior probabilities of current or future hypotheses top-down in a context-dependent way.
