"The evidence is very strong… It's a very clear conclusion last year that represents very strong evidence that should be taken into account.
In other words, within BP1A or BP1B, mothers and newborns only share slightly more similar profiles than randomly chosen pairs of individuals, but the clear differentiation of these classes nevertheless represents very strong transmission of leukocyte expression from mother to newborn.
The deep network generated by cascade algorithm can represent very strong non-linearity.
But you have to remember that there are a growing number of people who grew up playing games and still arethose lifetime players represent very strong growth..
(2) Theorems 2.7 2.16 represent very strong variants of the results in [3, 8, 11, 13] in the sense that the commutativity or compatibility of the mappings and is replaced by the hypothesis that is a Banach operator pair, needs not be linear or affine, and needs not be -nonexpansive.
Cases were set to 1 and MAP negative controls to 0. Uncorrected p-values <5×10−7 were accepted to represent very strong proof of genome-wide association, while p-values between 5×10−7 and 5×10−5 were considered as moderately significant associations.
Biological markers represent very strong tools for monitoring the progression of cancer and estimating the effectiveness and safety of new therapeutic agents (Cho, 2007).
A correlation coefficient value ≤ 0.35 is generally considered to represent a weak correlation, 0.36 to 0.67 to represent a moderate correlation and 0.68 to 1.0 to represent a strong correlation with coefficients ≥ 0.90 representing very strong correlations [ 15].
Each immunostained tissue section was assessed and staining intensity in benign epithelial, cancer (Gleason grade G3/G4) and stromal regions was scored from 0 to 4 with 0 representing negative staining and 4 representing very strong positive staining.
Uncorrected comparison-wise p-value of p < 5 × 10-7, whish is generally accepted to represent very strong proof of genome-wide association [ 47, 48], was used to identify significant marker-trait associations for all traits.
For reporting purposes, MIPs within the ranges (0.05, 0.25] or [0.75, 0.95) represent positive evidence, (0.01, 0.05] or [0.95, 0.99) represent strong evidence, and [0, 0.01] or [0.99, 1] represent very strong to decisive evidence, approximately following the corresponding Bayes factor interpretations in Kass and Raftery (1995).
