Sentence examples for substantially more variation from inspiring English sources

Thus there is substantially more variation in the quality of human predictions than of ML predictions.

The new sequence suggests that there is substantially more variation between humans than previously recognized and pushes personalized medicine a step closer.

Within rivers, sexual selection for orange colour is generally stronger in low- than in high-predation populations [24], [26], [44], [45], however there is substantially more variation in all colour traits among low-predation males from different rivers than high-predation males [20], [25], [26].

Although there is some variation within a placenta, there is substantially more variation between individuals than within an individual [ 27].

There appears to be substantially more variation in substitution rates based on recent calibration points compared to those from older calibration ages in both life history categories (Fig. 2).

Compared to the SCMGENE subtypes, the PAM50 subtypes explained substantially more variation in gene expression for both PC1 and PC2 (Fig.  2a, b), with these components being especially prominent for the separation of the Luminal A (or ER+/HER2−/Low Proliferative) and Luminal B (or ER+/HER2−/High Proliferative) subtypes.

Geographic distance constrained substantially more variations (12.9 %) than seawater variables (6.4 %), whereas grazing rate independently explained 12.8%% of the observed variation (Fig. 4).

The health variables models explained substantially more variance.

Whole-genome sequencing (WGS) can uncover substantially more genetic variation than traditional single-nucleotide polymorphism (SNP) arrays, thus explaining a larger fraction of human phenotypic diversity [ 3, 4].

Compared with traditional single nucleotide polymorphism (SNP) arrays [ 20], WGS can generate target DNA sequences and identify substantially more genetic variations, thus explaining a larger fraction of human phenotypic diversity [ 21].

Generally, we observe that the model fit is substantially more sensitive to variation in the parameters fmin, γ s, ω g, ω b than in the parameters find, α, γ s, A (compare the left and middle columns of Figure 3, where the effect of perturbations in these two subsets are displayed, respectively).