Table 4.

Distribution of training data for the RF classifier targeting interesting planets. Each row represents a different SNR level (with 0 indicating a noise-free spectrum), while each column is labelled with a three-digit binary code indicating the presence (1) or absence (0) of CH|$_4$|⁠, O|$_3$|⁠, and H|$_2$|O, respectively (e.g. ‘010’ means no CH|$_4$|⁠, presence of O|$_3$|⁠, and no H|$_2$|O). The values in each cell (in thousands) denote the total number of noisy spectra generated for that specific atmospheric configuration.

SNR000100010001110101011111Airless
130060606057.657.657.676.8100
330060606057.657.657.676.8100
630024242438.438.438.446.08100
1030024242438.438.438.446.08100
030060606096969657.6100
SNR000100010001110101011111Airless
130060606057.657.657.676.8100
330060606057.657.657.676.8100
630024242438.438.438.446.08100
1030024242438.438.438.446.08100
030060606096969657.6100
Table 4.

Distribution of training data for the RF classifier targeting interesting planets. Each row represents a different SNR level (with 0 indicating a noise-free spectrum), while each column is labelled with a three-digit binary code indicating the presence (1) or absence (0) of CH|$_4$|⁠, O|$_3$|⁠, and H|$_2$|O, respectively (e.g. ‘010’ means no CH|$_4$|⁠, presence of O|$_3$|⁠, and no H|$_2$|O). The values in each cell (in thousands) denote the total number of noisy spectra generated for that specific atmospheric configuration.

SNR000100010001110101011111Airless
130060606057.657.657.676.8100
330060606057.657.657.676.8100
630024242438.438.438.446.08100
1030024242438.438.438.446.08100
030060606096969657.6100
SNR000100010001110101011111Airless
130060606057.657.657.676.8100
330060606057.657.657.676.8100
630024242438.438.438.446.08100
1030024242438.438.438.446.08100
030060606096969657.6100
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