I apologize for a weird question and without providing replicable example.

I fit a multilevel regression model with brms package in r. The model has 4 fixed effects with the interaction between them: age (2 levels), experiment number (2 levels), confidence (continuous with a linear (c1) and quadratic (c2) term) and accuracy (2 levels). For the matter of my work, I am interested in the two-way interaction between experiment number and confidence (c1). Now, when I want to explore this further, I use the following code but it gives me marginal means and contrasts that includes all the variables.

    emm <- emtrends(
  fitted_model,
  var = "c1", by = c("Experiment_number"),
  at = list(confidence1 = 0, c2 = -32.9)
)
describe_posterior(
  emm,
  test = "pd", ci = 0.95, centrality = "mean", dispersion = TRUE
) %>%
  bind_rows(
    describe_posterior(
      pairs(emm),
      test = "pd", ci = 0.95, centrality = "mean", dispersion = TRUE
    )  
  ) %>% 
  mutate(pd = percent(pd, .01)) %>%
  kbl(digits = 2,
      caption = "linear trend contrasts") %>% 
  kable_classic(html_font = "Arial", full_width = FALSE)

This gives me the following output. As you can see, this output includes all other variables and contrasts. Is there a way to exclude other variables and get an output only for the interaction between experiment and c1? Note that this is only half of the output.