“highly significant”

The analysis identified a significant effect of time ( p < 0.001); a significant group effect, favoring active warming ( p = 0.039); and a highly significant time × group interaction ( p < 0.001), demonstrating greater intraoperative thermal stability in Group 1 ( Table 2 , Figure 2 ).

The results demonstrated that all three factors exhibited highly significant negative correlations with both archaeal and bacterial community similarity ( p < 0.001), indicating a typical distance-decay pattern.

All alpha diversity indices differed markedly among soil depths, with highly significant effects observed for depth ( p < 0.001).

Despite this similarity in cognitive level, both ASD groups displayed pronounced deficits on all components of the MABC-2 compared with their typically developing peers, with highly significant differences across manual dexterity, aiming and catching, and balance domains ( p < 0.001).

One-way ANOVA revealed highly significant treatment effects on circulating cTnT (F(3,24) = 32.166, p < 0.001), CK (F(3,24) = 23.908, p < 0.001), CK-MB levels (F(3,24) = 26.760, p < 0.001) and LDH (F(3,24) = 146.200, p < 0.001).

A PERMANOVA test based on Jaccard distance revealed a highly significant effect of the functional zone on the overall microbial community structure ( p = 0.001, Figure 4 e).

To confirm the previously obtained values, an analysis of variance (ANOVA) test was first conducted ( Table S3; Supplementary Materials ), with significance values less than 0.05 and showed highly significant differences across all treatments ( p < 0.001).

The overall model fit was highly significant (Adjusted R 2 = 0.2165, p < 0.001), indicating that the selected environmental factors could substantially explain the distributional variation in cryoconite bacterial communities.

The overall trend is highly significant ( p < 0.001).

PCA conducted separately within each subscale revealed clear and interpretable component structures, with acceptable sampling adequacy (KMO values ranging from 0.685 to 0.826) and highly significant Bartlett’s test results ( p < 0.001), confirming the suitability of the data for factor analysis.

Accordingly, age distribution differences were highly significant ( p < 0.001), with isotretinoin over-represented in adolescents and topical retinoids more frequent in children and older adults, potentially reflecting off-label or non-acne use of topical agents.

Statistical evaluation using the Mann–Whitney U test confirmed that this difference was highly significant ( p < 0.001).

arvensis GLMM with binomial dependent variable (capsules obtained 0 seeds or non-zero seeds) showed that the treatment effect was highly significant with (estimate = 1.44, χ 2 = 58.2, df = 1, p < 0.001, Figure 3 ).

The multivariate test revealed that all main effects (species and extraction) and their interaction were highly significant ( p < 0.001), indicating that both factors, independently and in combination, significantly influence the overall phenolic composition ( Table S4 ).

In Chardonnay, NDVI exhibited a strong and highly significant negative correlation with °Brix in 2023 (r = −0.86; R 2 = 0.74; p < 0.001), indicating that low-vigor vines accumulated higher soluble solids at harvest.

In a multivariate linear regression model, the WV experienced and poor work ability were highly significant predictors of work-related stress ( p < 0.001).

Analysis of variance revealed that both the main effects and the interaction between 6-BA and NAA concentrations on the callus induction rate were highly significant ( p < 0.001), with 6-BA exerting the most substantial influence (F = 69.969, p < 0.001).

All examined community-level factors demonstrated highly significant associations with IMF ( p < .001).

In the case of RTAB, the intercept was not statistically significant (0.0086; SE = 0.035; p = 0.807), yet the effect of POD 1 remained highly significant (−0.0054; SE < 0.001; z = −11.72; p < 0.001), although with a smaller magnitude.

The best model for nare length included tarsus, sex, and site and had lower explanatory power (adjusted R 2 = 0.197) but was still highly significant ( p < 0.001).

Moreover, correlation analysis demonstrated a highly significant relationship between the predicted and manually annotated CA values, with a correlation coefficient of 0.98 ( p < 0.001; Supplementary Fig. 2 b).

Assessing the effect direction of the identified neonatal mortality predictors using logistic regression The top three variables most relatively important in the XGBoost model were also highly significant in traditional logistic regression (early breastfeeding, birth weight, and household size, all with p-values <0.001).

001; and β=0.02, SE 0.003) and staff (β=0.01, SE 0.001; β=0.51, SE 0.002; and β=0.05, SE 0.004) were highly significant, with all the outcomes at the significance levels of P <.001 and P <.001 respectively.

Model analysis demonstrated a highly significant time effect across all models (all P < 0.001), indicating a marked increase in B-line scores over time.

Analysis of variance revealed that temperature (A), catalyst loading (D), and the methanol-to-oil ratio (C) were highly significant ( p < 0.001), whereas reaction time (B) showed moderate significance ( p = 0.0645).