storing list results into a table or data frame format

I am working with 4 lists of confusion matrices and I want to store the results in a table.

In order to get the confusion matrix list I created the following example:

data(iris)

data <- list(
iris %>% filter(Species != "setosa") %>% mutate(Species_to_predict = +(Species == "virginica")),
iris %>% filter(Species != "setosa") %>% mutate(Species_to_predict = +(Species == "virginica")),
iris %>% filter(Species != "setosa") %>% mutate(Species_to_predict = +(Species == "virginica")),
iris %>% filter(Species != "setosa") %>% mutate(Species_to_predict = +(Species == "virginica"))
)

LogitModels <- map(data, ~glm(formula = Species_to_predict ~ Sepal.Length + Sepal.Width + Petal.Length + Petal.Width,
               data = ., family = "binomial"))

Preds <- map2(
  .x = data,
  .y = LogitModels,
  ~predict(.y, newdata = .x, type = "response")
) %>% 
  map(., ~data.frame(.) %>% 
        setNames("Prediction") %>% 
        mutate(pred_status = ifelse(Prediction > 0.5, 1, 0)))

full_data <- list(
  cbind(data[[1]], Preds[[1]]),
  cbind(data[[2]], Preds[[2]]),
  cbind(data[[3]], Preds[[3]]),
  cbind(data[[4]], Preds[[4]])
  )

CM <- full_data %>% 
  map(.,
  ~caret::confusionMatrix(
    as.factor(..1$pred_status),
    as.factor(..1$Species_to_predict),
    mode = "everything",
    positive = "1"
    )
  )

Once I have the confusion matrix I compute a calculation using:

Table <- list(
  TP <- CM %>% 
    map(., 
        ~as.numeric(.x$table[[1]])
    ),
  FP <- CM %>% 
    map(.,
        ~as.numeric(.x$table[[2]])
    ),
  FN <- CM %>% 
    map(.,
        ~as.numeric(.x$table[[3]])
    ),
  TN <- CM %>% 
    map(.,
        ~as.numeric(.x$table[[4]])
    )
)

result1 <- pmap_dbl(Table, ~ ((..1 * ..4) - (..2 * ..3))/sqrt((..1 + ..2) * (..1 + ..3) * (..4 + ..2) * (..4 + ..3)))

I also compute the AUCs.

AUCs = full_data %>% 
  map(., ~pROC::auc(as.numeric(.x$Species_to_predict), as.numeric(.x$pred_status)))

Finally I extract some further statistics from the confusion matrix (for only the first confusion matrix in the list).

data.frame(
  Accuracy = CM[[1]]$overall[[1]],
  Sensitivity = CM[[1]]$byClass[[1]],
  Specificity = CM[[1]]$byClass[[2]],
  Precision = CM[[1]]$byClass[[5]],
  F1 = CM[[1]]$byClass[[7]]
) %>% 
  t()

Which gives this output:

            [,1]
Accuracy    0.98
Sensitivity 0.98
Specificity 0.98
Precision   0.98
F1          0.98

I want to compute the above for all 4 confusion matrices in the list and add the additional calculations. That is the final output being a data table where I can use stargazer to put into a LaTeX table.

Expected output:

            [,1] [,2] [,3] [,4]
Accuracy    0.98 0.98 0.98 0.98
Sensitivity 0.98 0.98 0.98 0.98
Specificity 0.98 0.98 0.98 0.98
Precision   0.98 0.98 0.98 0.98
F1          0.98 0.98 0.98 0.98
AUCs          1    1    1    1
result1     0.96 0.96 0.96 0.96