## 2 Materials and Methods
### Study Risk of Bias Assessment  
In support of the PRISMA flow diagram, an adapted Critical Appraisal Skills Programme (CASP) systematic review checklist was used to assess the validity of the results obtained from studies, ascertain the study results, and evaluate their impact and applicability.  
* Q1. Is the research related to both machine learning and the classification of transformer faults based on DGA data?
* Q2. Does the research stipulate the analysis methodology used in the study?
* Q3. Does the research specify the performance accuracy of the methods used for DGA interpretation?
* Q4. Does the research stipulate DGA data sources and data size?
* Q5. Does the research consider DGA applications for transformers only and not tap changers and bushings?  
To address the data quality and risk of bias, a set of assessment questions for the literature papers analyzed was used with a scaling matrix used to assess the quality of the papers primarily consisting of three criteria, \"yes\" as a score of \"1\", \"partially\" as a score of \"0.5\", and \"no\" as a score of \"0\". A summary of the results of the studied papers is tabulated in Table 4.  
\begin{table}
\begin{tabular}{l l l l l l l l l} \hline
**Paper ID** & **Q1** & **Q2** & **Q3** & **Q4** & **Q5** & **Total** & **\%** \\ \hline
1, 2, 4, 5, 6, 7, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, & & & & & & & \\
24, 25, 29, 30, 31, 32, 34, 35, 36, 37, 38, 39, 40, 41, 42, 44, 45, 46, 47, & & & & & & \\
48, 49, 50, 52, 53, 54, 55, 60, 62, 66, 67, 68, 70, 71, 72, 73, 76, 78, 79, & 1 & 1 & 1 & 1 & 1 & 5 & 100 \\
81, 82, 83, 85, 86, 88, 90, 91, 92, 93, 94, 95, 97, 98, 100, 102, 104, 105, & & & & & & & \\
106, 107, 108, 110, 111, 112, 115, 116, 119, 121 & & & & & & & & \\ \hline \end{tabular}  
* 3, 8, 26, 27, 28, 43, 56, 58, 61, 63, 69, 74, 77, 78, 84, 89, 96, 99, 101, 109, 113, 114, 117, 118, 120, 122, 124  
\end{table}
Table 4: Data quality and risk of bias assessment.  
\begin{table}
\begin{tabular}{l l} \hline
**Criteria** & **Description** \\ \hline Paper Title & The title of the paper studied \\ \hline Publication Year & The year in which the paper was published \\ \hline Publication Type & The type of publication of the studied paper: \\  & journal or conference paper. \\ \hline Publishing Repository & Which repository was used to collect the papers \\ \hline Publication Country & The country in which the paper was published \\ \hline Primary Condition Monitored & The type of transformer fault that was studied \\ \hline Classification Method & The type of machine learning classification \\  & method: binary or multi-classification \\ \hline Algorithm Used & The type of machine learning algorithm used \\ \hline Algorithm Performance & The accuracy performance of the algorithm used \\ \hline Dataset Used and Their Source & The source of the DGA dataset used for analysis \\ \hline Algorithm Development Software Used & The software used to develop the \\  & machine-learning model \\ \hline Industrial Standard/Specification Used & The industrial specification referenced or \\  & adhered to \\ \hline \end{tabular}
\end{table}
Table 3: Key data items from literature.