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Figure 6 shows the accuracy (root mean square error) in inferring the concordance factor of clades (12) and (123), two clades in the species tree (fig. 1).
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This allows us to avoid the errors that are implicitly introduced in inferring the 3-D coordinates from the EDM.
Any uncertainties in inferring the intrinsic brightness of the indicators we observe will propagate into distance errors.
Using this approach, we independently verified correct alignment in inferring the position of all 23,232 arrayed elements detectable on this platform with no errors using these training images.
Under a null hypothesis of no effect, two kinds of errors in interpretation are possible inferring an effect where none exists (Type I error) and inferring no effect when in fact one exists (Type II error).
Although this is higher than error rates inferred in other sequenced avian genomes, such as the 0.05% rate estimated for zebra finch [ 15], it is likely to overestimate the true error rate, because some substitutions will reflect mis-alignments or genuine point mutations.
With regard to the latter, borderline traits in adolescents are associated with 'hyper-mentalising' errors (i.e., errors of inferring mental states in others without reasonable justification) [ 33], rather than the 'hypo-mentalising' errors (i.e., errors of failing to infer mental states) seen in our early psychosis sample.
We use this estimate to derive a time series of "clock error", defined as the difference in timing of two clocks, one based on a theoretically invariant time scale (terrestrial time) and one fixed to Earth rotation (universal time), and compare this time series to millennial scale variability in clock error inferred from ancient eclipse records.
In addition, the low values of the root mean square of error (RMSE) inferred that the estimated had an acceptable accuracy range.
In the upper panels, RF measures accuracy of the inferred topology only; an increase of 2 units indicates an average of 1 additional error per inferred tree.
In a series of tests the material variability throughout the ensemble of specimens, the entirety of specimen-specific material properties and the measurement error level are inferred under various uncertainties in the problem setup.
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