Barely Significant
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“extremely significant”

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This QTL hotspot on SSC 12 harbored additional extremely significant QTLs which explained more than 10% of phenotypic variances: the QTL for C18:2 was found with an F -value of 90.4 (nominal p-value 1.1×10 −36 ) and accounted for 15.9% of phenotypic variance, while the QTL for C20:4 was found with an F -value of 159.7 (nominal p-value 5.7× 10 −34 ) and explained 14.3% of phenotypic variance.
The DEGs between the two cultivars with extremely significant differences in the content of glutenin, crude fat, four non-polar amino acids (Alanine, Methionine, Leucine and Tryptophan) and two neutral amino acids (Cysteine and Serine) were enriched into four GO terms related to amino acid transport (Fig. 11 a).
This was particularly true of the first five mixtures in the series; in the other mixtures the absorption of agglutinin by the excess of agglutinable cells present also played a part; and in the last two, they apparently prevented agglutination, as in the experiments referred to in table II. This, of course, is extremely significant for transfusion; a few large clumps might cause serious or fatal embolism.
Nevertheless, the histopathological data (positive margins or parametria, lymph node metastasis, presence of residual tumor at hysterectomy and tumor size) could play an extremely significant role, taking into account that after controlling for these factors, the use of a uterine manipulator or unprotected colpotomy were no longer associated with worse outcomes [ 152 ].
The variance analysis results of response surface model in Table 3 show that, the regression model p < .0001, indicating that the model was extremely significant; the Lack of fit p (.0964) was higher than .05, which was not significant, indicating that within the test range, the predicted values of the regression model fitted the actual values, determination coefficient of the variable coefficient R 2 was 0.9772, showing that the regression model could explain the 97.7% variability of test data and the predicted values were highly correlated with actual values, and this model can be used to analyze and predict temperature stability. 3.2.
And, even if in some animals (such as humans) the PLR may confer but little advantage, “one should bear in mind that seemingly trivial advantages may become extremely significant in a competitive situation; thus an animal whose pupil can dilate a little more may acquire a distinct competitive edge at dusk, and this could make the difference between starvation and plenty.” ( Barlow, 1972, p. 3 ).