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This issue in fact leaves the door open for other potential explanations that do not require the explicit formulation of a prediction to explain such effects.
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Additionally, given that in serological studies the bioinformatics approaches are only marginally used, we consider that the successful application of a B-cell epitope prediction tool to explain our experimental outputs is per se an interesting finding.
A mechanical model of atomic movement and agglomeration, ultimately based on experience, would allow one to discover probabilistic empirical laws, to make predictions, and to explain relationships between different kinds of phenomena.
In addition, induced-fit docking (IFD) simulations and site of metabolism (SoM) predictions helped to explain the recognition of new potent steroidal aromatase inhibitors within the enzyme.
The reward prediction hypothesis seems to explain addiction by understanding it as a pathology of reinforcement learning.
A new logistic regression analysis was applied to these covariates (8) with the objective to obtain those with prediction power higher to explain the patient's outcome.
Reasoning agents in real-world environments rely on a solution to the Qualification Problem in order to make useful predictions but also to explain and recover from unexpected action failures.
These predictions can help to explain apparently 'maladaptive' hermaphrodite systems.
Dwell effects resulting in lower life than pure fatigue are observed in the prior experimental research while no proper prediction methods are available to explain the phenomenon.
The risk adjustment tool proved to have an acceptable level of prediction (R ≥ 0.55) to explain pharmaceutical expenditure.
A recent paper provided evidence in favour of this prediction, employing normalization models to explain the effects of attending to one of two stimuli that are presented inside the RFs of MT neurons (Ni et al., 2012).
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