“highly significant”

The interaction between AF and the Deep-minus-Surface score was highly significant, F(1, 1626) = 64.29, p < 0.001, indicating that the relationship between relative learning orientation and marks differed clearly by AF.

For the TNC‐pre model (Table 6 ), the intercept estimate was 6.544 (SE = 0.265), representing the mean TNC count in the BTC twin group and was highly significant ( t = 24.696, p < 0.001).

The 12 week EWL was highly significant (p < .001).

A p < 0.05 (*) was considered significant, p < 0.01 (**) was highly significant, and p < 0.001 (***) was very highly significant.

All these correlations were highly significant ( p < 0.001).

1) = −3.99, P < 0.001 and with ample food (8.00 ×10 −1 mg/L algae) plus or minus 1.11 ×10 −2 mg/L MPs was highly significant t (d.f. 1) = 4.59, P < 0.001 since there was no mortality in the treatment without MPs ( Table 3 ).

Statistical significance was defined as follows: p>0.05, not significant (ns); p<0.05, significant; p<0.01, highly significant; and p<0.001, extremely significant.

The abundance of Chloroflexi had a markedly negatively relationship with available potassium ( r = −.99, p < .001) and total carbon ( r = −.82, p = .001), and the Bacteroidetes exhibited a highly significant positive correlation with available potassium ( r = .90, p < .001) and total carbon ( r = .81, p = .001), then Nitrospirae ( r = −.95, p < .001) were significantly negatively correlated with soil available potassium.

Statistical analysis using the χ 2 test revealed a highly significant result ( p <0.001), indicating that the observed changes in severity scores from week 0 to week 4 were not due to chance.

The viscosity variations were highly significant over the hemicycles (F 2.7,53.2 = 16.431, p < 0.001, η 2 p = 0.45), but no effects were detected for the interaction between hemicycle and group (F 2.7,53.2 = 0.794, p = 0.489, η 2 p = 0.04).

Next, we computed highly significant (FDR-corrected P -value < 0.001) differentially expressed genes between all pairs of tissues.

Genetic differentiation and nuclear migration rates between species AMOVA results showed that genomic differentiation between species was low (10.99 %), but still highly significant ( P < 0.001; Table 4 ).

The linear trend was highly significant, t = 5.7, p < 0.001 and the effect of legalization also had a significant additional impact of the number online calls, t = 2.2, p < 0.05.

For MFCC2 with fmax = 12 kHz, there was a highly significant effect of gender (males were higher, p <0.001) and a significant effect of dataset (CLAC values were lower, p <0.05) with no significant effect of age.

LMM analysis demonstrated that the main effect of stage was highly significant for all hemodynamic variables, including systolic blood pressure, diastolic blood pressure (DBP), MAP, and CPP (all P < 0.001, Table 4 ), indicating substantial changes in hemodynamic status from the compression stage through to the post-ROSC period.

Baseline cystatin C level had a direct and highly significant linear relationship with baseline creatinine level of patients ( P < 0.001 ; r: 0.926). ).

There were few significant differences in neighbourhood characteristics, except for parks ( p = 0.040) and health service destinations ( p = 0.019) for those with and without diabetes; however, there was a highly significant difference in both slope mean ( p < 0.001) and slope tertile distribution ( p < 0.001) between adults with and without diabetes.

One-way ANOVA showed that this difference was highly significant statistically ( F: value 5.653, P < 0.001) ( Table 2 ).

A highly significant positive correlation was obtained between tocopherol content and α-tocopherol (r = 0.97, ***P < 0.001).

Spearman’s correlation analysis also revealed a highly significant positive correlation between the patients’ knowledge and attitude scores (r=0.21, p=<0.001).

Notably, DHRS9 and CHGB exhibited higher median values in the experimental group, whereas TNNI1 and DNER showed lower median values, with highly significant differences ( P < .001).

Our results identified several factors associated with teenage pregnancy: age was a significant factor, with teenagers aged 18–19 years having a much higher likelihood of pregnancy (12.3%) compared to those aged 15–17 years (1.6%), with a highly significant p < 0.001.

Across sessions, the shift in cue–reward index from adolescent Session 1 to Session 7 was highly significant in ST subjects ( Z = 6.59; p < 0.001, Wilcoxon rank-sum test) but not in GT subjects ( Z = 0.08; p = 0.94).

A post hoc statistical analysis showed that the age (as a covariate) of the population included in the study has no effect ( P = 0.749) in the highly significant clinical improvement ( P < 0.001) obtained with MV130 when compared with placebo.

However, a highly significant difference was found among the monthly average sizes for each sex ( p < 0.001), indicating that the captured population size varied considerably throughout the study period.