## 2 Materials and Methods
### Data for the Environmental Impact Assessment (EIA)  
The EIA was conceived as an evaluation tool with the goal of identifying and assessing the environmental impact of an activity in advance [39]. As a result, the conclusions obtained from an EIA are intended to support decision-making regarding the implementation of policy or engineering interventions for environmental management. However, there exists an uncertain regulatory landscape in relation to the EIA methodological approach, particularly in the definition of a procedural application that can be both effective in pursuing the general objectives of environmental assessment and suitable for different environmental scenarios. In this context, there is a common understanding that an EIA needs to comply with the national and regional legislative framework of decision-making within which it operates [40].  
Notwithstanding this rigidity, at this point, there is a great opportunity to develop modern data-driven approaches that put the focus on the data and the environmental factors and not so much on stringent criteria applied in one or another jurisdiction for the evaluation of impacts. On this basis, this research explores the development of an EIA that treats a priori all environmental factors equally, gathering the data on its corresponding attributes or variables which will constitute the input of an AutoML process, based on Bayesian learning, that will uncover the existing relationships and impacts among the different factors.  
In total, 10 environmental factors were defined, which are characterized by a total of 40 attributes. Table 1 presents the 10 environmental factors clustered according to the potentially identified attributes that can be affected by the presence of mining activity in the study area of Vilarbaci. For each attribute, based on the analysis of the possible future environmental impacts associated with the mining activity evaluated in the field, a value between 0 (no impact) and 10 (huge impact) was assigned based on the degree of negative impact that this area may suffer as a result of the exploitation of slates. For each attribute, up to 60 different values were gathered in different locations within the study area.  
Finally, it is important to remark that the scale of values assigned to the different attributes is intended to maintain the greatest possible similarity with the current narrative used in Spanish legislation [41] when categorizing the level of environmental impact. In practical terms, this does not affect the AutoML process proposed in this article; however, it may facilitate its interpretability by the public administration. Therefore, from a conceptual viewpoint, the attributes results are interpreted as follows:  
* **Compatible environmental impact** (0-3): Recovery is immediate after the activity ceases, and no protection or mitigation measures are necessary.
* **Moderate environmental impact** (4-6): Protective measures or a recovery time interval are required after the activity ceases.
* **Severe-critical environmental impact** (7-10): It is necessary to apply protection and restoration measures, with the possibility that recovery after the cessation of activity is not possible given that its magnitude is above the acceptable threshold.