## 1 Introduction
This work focuses on defining \"when\" a potential mass removal event might occur [3]. The value of the present research lies in the existence of a geotechnical history specifically to the study area in Cortinas, as documented in [2], constituting a fundamental input for building a baseline for this investigation and future studies. Geologically, the study area is located on the northeastern flank of the Eastern Corolliera of the Andes in Colombia. Observing the three-dimensional model of the available satellite images of the area reveals a high degree of complexity in terms of its stability, with the geoforms confirming this assessment. The first documented record dates back to 1990, when, according to local people and oil transportation engineers, there was a landslide similar to the one in 2021. Around 2015, during an extreme winter season, multiple regional landslides occurred. The largest recorded landslide in the area prompted one of the oil and gas companies operating in the sector to initiate an investigation process, indicating that, at present, progress is being made, with the possibility of reducing failures that interrupt gas transportation operations; however, no failure was recorded in the Cortinas field at that time. In January 2020, a failure was recorded in the gas transportation line in the Cortinas area (Slide D 2021) despite the fact that no extraordinary rainfall preceded the event to induce considerable movement of the slope. In 2021, the slope failure occurred \"suddenly\" following a rainfall event that was perhaps the most extreme in recorded history. Paradoxically, in the current year (2024), rainfall levels similar to those in 2021 occurred again but without generating significant slope displacements, as confirmed by topographic monitoring records. This paradox is precisely what creates uncertainty regarding how the failure mechanisms work in these contexts, particularly regarding what could have been predicted. To reduce the uncertainty introduced by this paradox, in addition to the monitoring of triggering factors, we included, as a novel approach, the study of changes in the conditioning factors over time. Using the concept of AGD, we outline a path toward prediction, constituting a baseline for future research aimed at improving prediction accuracy. Thisis fundamental since it is necessary to be able to act in advance of landslides. In this way, an alert could be generated to save lives and/or infrastructure, as well as, for example, for hydrocarbon transportation companies to act by interrupting the flow and avoiding environmental and social impacts. As pointed out in the first article of this research [2], our main source of data corresponds to the information compiled through our own work covering 33 years of observation that constitute the history of the Cortinas sector and its surroundings, as well as the information from historical records of the Information System of Mass Movements (SIMMA) [4], Institute of Hydrology, Meteorology, and Environmental Studies (IDEAM), and Colombian Geological Service (SGC) [4] in relation to past landslides, rainfall, and earthquakes. According to the literature, different methodologies are currently used for landslide prediction, such as probabilistic models focused on defining landslide susceptibility areas and statistical models of a subjective linear nature, similar to the probabilistic ones, which focus on pre-existing landslides [5]. However, these models are often unable to effectively represent complex landslide cases because the relationship between problems based on natural phenomena and their triggering factors is not always linear [6; 7]. Additionally, they lack an exhaustive spatial analysis that allows evaluating the presence of spatial dependence or auto-correlation between global or local landslides [8; 9], inducing important errors. In contrast, methods based on spatial statistics focus on triggers and their thresholds aimed at defining areas of susceptibility, which are distorted by the AGD concept.