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Models had high R2 values, suggesting higher taxon identity and a gradient of vegetation index together explain most of the variation in species richness in our data.
The four models were improved using an iterative approach in which a threshold for cover was established, and all models had high sensitivity values when tested on an independent dataset.
The models had high R2 values (>0.9500) which were able to predict reliable optimum total solids yield (55.59%), glucose concentration in pretreated residue (26.51 g/l), xylose concentration in pretreated residue (8.63 g/l) and xylose concentration in pretreated liquor (15.15 g/l).
60 evodiamine analogs were used for constructing the best comparative molecular field analysis (CoMFA, q2 = 0.729, r2 = 0.985) and comparative molecular similarity index analysis (CoMSIA, q2 = 0.746, r2 = 0.989) models, the models had high predictive ability, and the contour map was in good agreement with the generated pharmacophore features.
The CVs as calculated from the amount of displacement under loading in the experimental, contact, and fixation models were about 5%to10%0%, and all models had high reproducibility with respect to implant displacement under loading.
All models had high NPVs (≥97%).
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By contrast, tumor tissues from PyMT-B6 and KPC models had higher Csf3 levels compared to normal mammary and pancreas tissues (Fig. 5a).
This implies that the ANN models had higher errors associated with their better predictions.
The statistical results clearly illustrated that the consensus models had higher predictive accuracy ((q_{ext}^{2}) = 0.669 0.689) than any individual model.
Mice from the AxD models had high-enough levels of GFAP to allow dilutions from individual samples, typically 1 16 1 120.
All more complicated models had higher Akaike information criterion (AIC) scores.
Related(20)
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