Sentence examples for lower number of errors from inspiring English sources

On the other side, the significantly lower number of errors of RSV supplemented animals in this spatial reference memory task suggested a positive effect of RSV on hippocampus activity or functions.

In that study, the note which was associated to a lower number of errors, in both AP and NAP musicians together, was the note D. This result, which has been observed thanks to the large sample size, can be explained along with the present evidence by reference to the fact that the solfège name of D is Re, which is the sole note that does not have a companion regarding vowel similarity.

It is worth noting the unusual result of a lower number of errors in latent space than in data space.

As expected, under ERROR condition children made a lower number of errors (i.e. touched the walls of the labyrinth less often); time used to complete each task instead was not significantly different.

Women with the Val/Val genotype also committed a lower number of errors below the mean (M = -0.30, SE = 0.19) than did the Met/Met genotype, which performed above the mean (M = 0.81, SE = 0.33).

Women carriers of the Val/Val genotype performed better in executive functions, as indicated by a lower number of errors committed in comparison with the Met/Met or Val/Met groups.

The z-score denoted that women carriers of the Val/Val genotype performed better, as indicated by a lower number of total errors committed below the mean (M = -0.56, SE = 0.22), than the Val/Met (M = 0.31, SE = 0.30) or the Met/Met (M = 0.21, SE = 0.15) groups, both of which committed errors above the mean.

In agreement with the previous study, we have shown that experience with computer navigation in TKR results in a lower number of intraoperative cutting errors.

It appeared that higher composites on communication and openness, feedback and communication about error and non-punitive response to error were associated with lower number of events reported.

For an identity threshold of 99%, the human metagenomes were classified correctly with lower accuracy, caused by the lower number of possible matching sequences due to the introduced error rate above 1% using a 1% average error rate.

Because the fitness function of EMD is weighted from the lower predictive error and the lower number of intervals, the attributes that do not use to create the classifier model mostly generate null cut-point.