## 2 Materials and Methods
To address this, we utilized an _in-house_ open-access tool called Ecotox-curator (available at [[https://github.com/ncordeiro/Ecotox-curator](https://github.com/ncordeiro/Ecotox-curator)]([https://github.com/ncordeiro/Ecotox-curator](https://github.com/ncordeiro/Ecotox-curator)), accessed on 14 June 2024), which provides a graphical user interface (GUI) for automated data curation, starting from datasets downloaded from the ECOOTOX database. The overall methodology of this tool for data curation is delineated in Figure 1.  
Briefly, Ecotox-curator assists users in a two-step data curation process:  
1. **Data Selection and Preprocessing:** Users provide the downloaded raw ECOOTOX dataset file (_csv_ format), and a separate file (\"First_input.csv\") specifying the desired columns for further processing. For example, in this work, the input file contains columns and values such as (a) SN--a serial number manually created to track the data points in the original dataset, (b) CAS number (required), (c) Chemical  
Figure 1: Methodology adopted for data curation for mt-QSTR modeling using the Ecotox-curator tool. name, (d) Species Scientific Name, (e) Species Group, (f) Conc 1 Type (Standardized), (g) Conc 1 Mean Op (Standardized), (h) Conc 1 Mean (Standardized), (i) Conc 1 Units (Standardized): AI mg/L, (j) Endpoint: LC50, EC50, and (k) Observed Duration (Days). 2. Additionally, the tool requires a specific cut-off value to define 'toxic' and 'non-toxic' classes. As mentioned earlier, a cut-off value of 5 mg/L was used in this work. The tool automatically saves a new file (\"FirstFile_forChecking.csv\") containing the specified columns along with the activity column (i.e., 'Active'). Basically, in this stage, the tool collects those columns that are necessary for modeling and removes unnecessary data, as specified by the users. Users can then manually check and modify \"FirstFile_forChecking.csv\" if necessary. For example, we created a new 'Time' category (Long, Medium, Short) based on the 'Observed Duration (Days)' column and removed irrelevant values like \"NR\" (Not Reported). 3. **Duplicate Removal and Conflict Resolution:** Once satisfied with the preliminary data, users should upload the modified \"FirstFile_forChecking.csv\" and a separate file (\"CAStoSMILES.csv\") linking CAS numbers to their corresponding SMILES notations (which ECOTOX does not provide). Tools like the Python-based CIRpy (available at [[https://github.com/mcs07/CIRpy](https://github.com/mcs07/CIRpy)]([https://github.com/mcs07/CIRpy](https://github.com/mcs07/CIRpy)), accessed on 16 June 2024) can assist in SMILES generation, but manual correction might be needed for CAS number formatting (missing hyphens in ECOTOX data). Alongside these two files, another input file (\"Second_input.csv\") is needed at this stage. This file specifies the column names to be treated as final experimental elements for further processing. In this work, the following column names were included: (a) Species Scientific Name (_sn_); (b) Species Group (_sp_); (c) Conc 1 Type (Standardized); (d) Endpoint; and (e) Time. In this stage, the duplicated data points are identified from the SMILES notations and experimental elements. Finally, the tool generates two output files: * _\"NoDuplicates.csv\"_: Contains data points without duplicates or duplicates with consistent activity classifications (all toxic or all non-toxic). Data points from this file are used for model development and validation. * _\"DupConflict.csv\"_: Contains data points with conflicting duplications (e.g., data points classified as both 'toxic' and 'non-toxic'). Data points from this file were not considered for modeling since conflicting activity classes were found. **Descriptor calculation. ** In this study, 1141 EPA (T.E.S.T.) descriptors (797 2D descriptors and 344 3D descriptors) were calculated for the dataset compounds using the OCHEM webserver [17]. These descriptors were generated through the Toxicity Estimation Software Tools (T.E.S.T.)