Is there a contradiction between the results of the mixed-effects model and those of the pairwise comparisons?

I am comparing two groups across six different time points using a mixed-effects model. No statistically significant group-by-time interaction, which is my primary interest. Here is the code: model1 = lmer(score ~ group * time + BMI + gender + prothesis.design + PCL + (1 | patient), data = data.frame, REML = T, contrasts = list(group = contr.sum, time = contr.sum)) Anova(model1, type = 3, test.statistic = "F") However, when I perform pairwise comparisons at each time point for data presentation and graphing, the first time point shows a significant difference (the adjusted confidence interval does not include zero). Here is the code: emm.hss = emmeans(model1, ~ group * time, adjust = "bonferroni") pairs(emm.hss, by = "time", adjust = "bonferroni") confint(pairs(emm.hss, by = "time", adjust = "bonferroni")) Is this a contradiction or a comparison based on different metrics? If it is not a contradiction, which result should I prioritize in my reporting, and how should I address it? Thanks in advance.