Subprocess analysis analysis: The default value is FALSE, indicating that the function does planning.
Initially the field is set to F (false) indicating no modification, it is set to T (true) when there is a modification by itself or a replication update from some other node is received.
However, of the large number of predicted targets for each microRNA a significant fraction is false, indicating there are also other parameters, yet to be discovered, that determine microRNA-target association.
False alarm indicates an empty channel detected busy, and the ratio is the number of false alarms to the number of total attempts.
Indeed, 20 years' worth of social science research on false confessions indicates that having recorded interrogations would dramatically increase the ability of prosecutors, investigators, jurors and judges to assess the validity of a confession.
A false positive indicates that SpoMBEL1693 predicts a viable phenotype while the in vivo result shows a lethal phenotype (Table 1).
The cutoff point corresponding to the optimal balance of true versus false positives indicates the best threshold for discriminating insulin-resistant individuals from insulin-sensitive individuals.
GeneralizationSet has two boolean attributes, viz., isCovering (default value is false), which indicates whether or not every instance of a general classifier is also an instance of at least one of its specific classifiers, and isDisjoint (default value is false), which indicates whether or not the set of specific classifiers in a generalization have an instance in common.
The performance of this ad hoc truncation apparently leads to better retrieval at small number of false positives, indicating the existence of false hits whose evidence peaks are homologous to that of the true positive(s) associated with a spectrum.
A false discovery rate of 0% indicates no false positives; a false discovery rate of 100% indicates a completely random signal.
