"reliable confidence" is a correct and usable phrase in written English.
You can use it when referring to a sense of confidence that is based on a solid, reliable foundation. For example: "His reliable confidence made it easy for him to take on any challenge that came his way."
As Web-based applications become more robust and reliable, confidence goes up, but services are not bulletproof.
As Web-based applications have become more robust and reliable, confidence has risen as well, but services are not bulletproof.
For very difficult classification problems with a high error rate reliable confidence estimation would be most desirable.
Here we present an overview of the steps necessary for effective outlier removal, error propagation and estimation in order to provide reliable confidence limits for the stress value obtained.
In order to obtain reliable confidence interval estimates, we suggest increasing the simulation times by 100 at each step, and the final results can be obtained when the values stabilize within consecutive steps.
This result provides the inventory forester with some scope to design sampling procedures that will be practical and operationally efficient while avoiding bias and still producing reliable confidence intervals.
This is because accurate, less-erratic and reliable "bootstrap confidence intervals" require replications in the order of 1000, which would have been computationally demanding and time consuming [32].
However, within the first group, only the animal clade received a reliable statistical confidence, and Opisthokonta as a whole was not resolved with enough statistical power.
Greater read depth (the number of times a nucleotide is sequenced) is advantageous for more reliable statistical confidence in the determination of a genotype at a position.
We used two independent approaches to derive more reliable, "high-confidence" datasets from our raw two-hybrid data: first, a simple approach based on the number of times a certain protein is found as prey: preys which are found more than 50 times (which is an arbitrary threshold) are likely to be unspecific interactors and thus have been excluded from the "TPA 50" dataset.
In this regard, the high- and intermediate-confidence peaks should be more reliable than low-confidence peaks due to the fact that any two different algorithms identified them as significant peaks (good signal-to-noise ratio).
