The External -Zamora (EXT-Zamora) and External -SAMPL9 (EXT-SAMPL9) datasets are taken from previous studies . The experiments conducted to measure the log P tol/w values in these datasets follow similar protocols to those used for obtaining the HF-Exp dataset. The EXT-Zamora and EXT-SAMPL9 datasets consist of 38 and 16 molecules, respectively (see Table ). Figure shows the density distributions of log P values for the LF-QC, HF-Exp, EXT-Zamora, and EXT-SAMPL9 datasets. The LF-QC dataset (red) shows a wide distribution range from -10 to 7, reflecting the extensive chemical diversity captured by the Quantum Mechanics (QM) dataset. The HF-Exp dataset (green) and EXT-Zamora dataset (cyan) have a more narrow and peaked distribution centered around -1 to 3 log P values, indicating that the experimental measurements are focused on a more homogenous set of species. The EXT-SAMPL9 dataset (purple) peaks around -1 to 3 log P values and 3 to 6 log P values, indicating differences in the molecules compared to the other datasets. The broad range of the LF-QC dataset shows the variability in computational predictions, while the narrower distributions of the experimental datasets (HF-Exp, EXT-Zamora, EXT-SAMPL9) reflect controlled conditions and specific chemical spaces. This variation is crucial for evaluating the performance and generalizability of predictive models across different types of data. Figure depicts the density distributions of solute molar masses for the LF-QC, HF-Exp, EXT-Zamora, and EXT-SAMPL9 datasets. The LF-QC dataset (red) shows a peak around 170 g/mol, indicating a relatively uniform distribution of molecules. The HF-Exp dataset (green) and the EXT-Zamora dataset (cyan) have a peak around 110 g/mol, suggesting a range of smaller molecule sizes. The EXT-SAMPL9 dataset (purple) displays a peak at higher molar masses, around 300 g/mol, indicating a tendency towards larger molecules.