## 3 Results
### Blind Study  
The first blind dataset that represents native petrol samples was input into the classification model. All the samples were correctly identified as native petrol samples. Table 4 represents the multi-class classification model's output for the prediction of the  
Figure 5: A representation of the hierarchy classification model for native, evaporated, and burnt petrol, and petrol burned on a substrate. -petrol sources. The Jet sample was misclassified as Esso; however, this can be explained by the low number of Jet petrol samples that were available for building the classification model. Esso and Shell displayed strong similarities in the \({}^{1}\)H selfTOCSY results for the four sets of olefins, which were minor compounds potentially contributing to the incorrect classification. Overall, the success rate of classifying the blind dataset of the native petrol samples was 80% compared to the currently used ATD-GC-MS method (30% classification) which uses target compounds and visual interpretation for the comparison of ignitable liquids (Table 7). The second blind dataset, which contained a combination of evaporated petrol samples (25% and 50%), petrol samples burned on their own and petrol samples burned on substrates (petrol samples extracted from cardboard substrate), was input into the model. The goal was to identify and link the petrol samples despite their evaporation status to their source (brand). Firstly, all the blind samples were correctly identified as weathered through the binary model (native vs. weathered). Then, the blind weathered dataset was input through the binary classifiers for each leaf. The NMR classification model displayed an overall accuracy of 78%; one of the Shell and one of the Texaco petrol samples was misclassified compared to the ATD-GC-MS method, which was not suitable for the identification and differentiation of petrol source (Table 8). The local classifier between Shell and Texaco had a 60% success rate, which could have contributed to the misclassification of the Shell petrol sample as a Texaco petrol sample. In addition, both petrol brands displayed similar \({}^{1}\)H selfTOCSY profiles for the four sets of olefinic compounds. The Esso petrol samples displayed similarities in their \({}^{1}\)H selfTOCSY profiles for the four sets of olefinic compounds to the Shell and Texaco samples investigated. \begin{table}
\begin{tabular}{l l l l l l} \hline \hline \multirow{2}{*}{**Sample N**} & \multirow{2}{*}{**Class**} & \multirow{2}{*}{**Native vs. Evaporated**} & \multicolumn{2}{l}{**Predicted Class by NMR**} & \multirow{2}{*}{**ATD-GC-MS**} \\  & & & & **Hierarchical Classifier** & & \\ \hline BLIND A & JET & native & ESSO & Identified as unique petrol source \\ \hline BLIND B & ESSO & native & SHELL & Identified as unique petrol source or similar to \\ \hline BLIND C & ESSO & native & ESSO & Sample G identified as similar to Sample C \\ \hline BLIND D & ESSO & native & ESSO & Sample D identified to be similar to Sample I \\ \hline BLIND E & TEXACO & native & TEXACO & Sample E and F identified as same petrol source \\ \hline BLIND F & TEXACO & native & TEXACO & Sample E and F identified as same petrol source \\ \hline BLIND G & SHELL & native & SHELL & Sample G identified as similar to Sample C \\ \hline BLIND H & BP M & native & BP M & Sample H and J were grouped with Texaco \\ \hline BLIND I & SHELL & native & SHELL & Sample I identified as similar to Sample D \\ \hline BLIND J & BP S & native & BP S & Sample H and J were grouped with Texaco \\ \hline \hline \end{tabular}
\end{table} 
Table 7: Summary table of the results of the blind dataset of native petrol sources with \(\approx\)60% correct classifications and \(<\)60% incorrect classifications.