The second dataset (hereafter referred to as "Norman dataset") was an extract of around 32000 chemicals (31722 chemicals), including their predicted 96h LC50 values for acute fish toxicity (Pimephales promelas) from the Norman SusDat database. This dataset included only the chemicals that were reported as within the applicability domain of the QSAR model developed by Aalizadeh et al, which was used for testing our model applicability, Figure . This is the model employed by Norman Network for their risk assessment and chemical management. When checking the overlap between the acute fish toxicity dataset and the Norman dataset, we observed around 100 common entries. We calculated 2757 1D (i.e. constitutional/count descriptors), 2D (i.e. structural fragments), and 3D (i.e. graph invariants) molecular descriptors, and PubChem fingerprints for both datasets using PaDEL software package, implemented via a python 3 wrapper called padelpy. Additionally, the name of the chemicals, their SMILES, and InChiKeys 37 were retrieved from the PubChem database 38 via pubchempy API. In order to identify the unstable descriptors-caused by the lack of convergence during the structural optimization-we performed the descriptor calculations for the acute fish toxicity dataset in triplicates. The descriptors were scaled by the maximum of each descriptor in the training set to minimize the impact of the descriptor magnitude on the final models. After scaling, the variance of each descriptor in the acute fish toxicity dataset was calculated and only the descriptors that had a variance below 0.1 were kept. We assumed that the stable descriptors for the acute fish toxicity dataset are also stable for the Norman dataset. Therefore, the descriptors for this dataset were calculated only once. Additionally, the maximum of each descriptor in the Norman dataset was compared to those from the training set (from the acute fish toxicity dataset). The descriptors that have this ratio larger than 100 were considered unstable and removed from both datasets, resulting in a total of 2036 final descriptors out of an initial 2780.