The article introduces a new method to analyze citation counts of scientific articles. By combining quantile regression and logistic regression, the model can better handle articles with very low citation numbers. The researchers found that adjusting the model to account for these low counts improved the accuracy of predicting citation numbers for more popular articles. This approach helps identify factors that influence whether an article will have low citations.