Sentence examples for range of the data set from inspiring English sources
Rather, we projected values outside this range onto a unitary line (45° slope), thus leaving that range of the data set unaltered.
We considered one compound, 2,3,7,8-tetrachlorodibenzo- p-dioxin (CAS 1746-01-6), an activity outlier because its log(1/LD50) value was −4.21 for the rat, which deviated significantly from the activity range of the data set.
In this approach, if the first and last fuzzy sets were defined according to the exact range of the data set, some membership functions, e.g., Supplementary Figure S1d j would be mostly ignored.
In contrast, a trend toward a positive correlation was observed for the HLA B∗5701 and S frequencies despite the small size and restricted range of the data set, resulting from the absence of this HLA variant in most populations (n = 8, p = 0.18).
Risk relationships for RPM intakes and CHD, diabetes mellitus and colorectal cancer were taken from published meta-analyses, presented in table 2. 8–10 The log of the RRs was assumed to be linearly related to absolute intakes across the full range of exposures in the data set, including the low (but not null) RPM intakes reported by self-declared vegetarians.
The grid of indices is shown in Fig. 2. Fig. 1 Global map of the Earth's magnetic anomalies relative to the CM4 main field model for year 1990 Fig. 2 Global map of the data set indices ranging from 11 to 47.
Although the depicted mitochondrial phylogeny is well resolved and comprehensive in terms of spanning the entire range of known jakobid diversity, the data set of mtDNA-encoded protein sequences is still too small to resolve the relationship of jakobids to other eukaryotes and in particular to the jakobid-like (in an ultrastructural sense; O'Kelly and Nerad 1999) malawimonads.
Black dots represent synthesis rates of individual proteins in excess of (1.5 × inner quartile range) of that data set.
In nine datasets containing both IHC-based ER positive and ER negative tumours, we observed a bimodal distribution of ESR1 expression, with coefficients of bimodality ranging from 0.619 to 0.776, whereas in the data set with only IHC ER negative tumours (JBI2) there was no visible bimodal distribution of ESR1 (coefficient of bimodality = 0.412, Supplement Figure S1).
Distribution of correlation coefficients has been studied for the range of probe radii for every structure in the data set.
Many methods employing machine learning techniques generate a wide-range of descriptors for each atomic site in the data set often including quantum chemical and electronic descriptors.
