Update paper.md

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@@ -32,7 +32,7 @@ The GTFS Segments (gtfs-segments) library is an open-source Python toolkit for c
 
 The choice of bus stop spacing involves a tradeoff between accessibility and speed: wider spacings mean passengers must travel farther to/from stops, but they allow the bus to move faster [@Wu2022]. Many US transit agencies have recently carried out *stop consolidation* campaigns that systematically remove stops, due partly to the perception US stop spacings are much narrower than those abroad. However, there are no reliable data sources to obtain current stop spacings despite the wide adoption of General Transit Feed Specification (GTFS) [@Voulgaris2023Predictors], because GTFS does not include data on stop spacings directly. Spacings must be computed from route shape geometries, stop locations, and stop sequences. A challenge is that stop locations are not placed on top of route shapes and therefore must be somehow projected onto the route's `LINESTRING`. To make spacings available for analysis, `gtfs-segments` use k-dimensional spatial trees and k-nearest neighbor heuristics to snap stops to routes and divide routes into segments for computation of spacings, as described below.
 
-`gtfs-segments` was designed for researchers, transit planners, students and anyone interested in bus networks. The package has been used in several scholarly articles [@Devunuri2024; @devunuri2023chatgpt; @lehe4135394bus] and to create databases of spacings for over 550 agencies in the US [@DVN/SFBIVU_2022] and 80 agencies in Canada [@DVN/QFTAPM_2023]. Several transit agencies, such as Regional Transportation District Denver (RTD- Denver), have used the package to visualize the effects of their bus stop consolidation efforts. Filtering functions allow the user to explore datasets, identify errors and compute specialized statistics.
+`gtfs-segments` was designed for researchers, transit planners, students and anyone interested in bus networks. The package has been used in several scholarly articles [@Devunuri2024; @devunuri2023chatgpt; @lehe4135394bus] and to create databases of spacings for over 550 agencies in the US [@DVN/SFBIVU_2022] and 80 agencies in Canada [@DVN/QFTAPM_2023]. Several transit agencies, such as Regional Transportation District Denver (RTD-Denver), have used the package to visualize the effects of their bus stop consolidation efforts. Filtering functions allow the user to explore datasets, identify errors and compute specialized statistics.
 
 # Functionality