## 4 Experiment and Evaluation
### Quantitative Evaluation Index  
Firstly, for the text-generation task, this study adopted the Rouge (Recall-Oriented Understudy for Gisting Evaluation) [48], BERTScore [49], and embedding-based similarity [50] as the evaluation indexes used to measure the quality of the generated text, and then to evaluate the accuracy and fluency of the generated text in multiple dimensions. These indexes can directly reflect the generated results of the model in actual application scenarios and provide an external measurement standard for model debugging. By combining these three indexes, the performance of the generative model can be evaluated in a more comprehensive and in-depth way. The evaluation index of Rouge is computed by counting the number of overlapping words or n-grams between the system-generated summary to be evaluated and the ideal \begin{table}
**Query** & **Output Without BM-RAGAM** & **Output with BM-RAGAM** & **Comments** \\ \hline \hline \multirow{8}{*}{What is an ocean front, and how does it affect marine life?} & \multirow{8}{*}{Ocean fronts are dynamic boundaries formed by the intersection of different water masses, often with different temperature, salinity, and density properties. The boundaries between these water masses are constantly changing and are affected by dynamic factors such as ocean currents, winds, and topography.} & \multirow{8}{*}{The BM-RAGAM retrieved correct misconceptions, clear definitions, and unambiguous answers.} & \\ \cline{1-1}  & & & \\ \cline{1-1}  & & & \\ \cline{1-1}  & & & \\ \cline{1-1}  & & & \\ \cline{1-1}  & & & \\ \hline \hline \end{tabular} \
\begin{tabular}{p{113.8 pt} p{113.8 pt} p{113.8 pt} p{113.8 pt}} \hline \hline \multirow{2}{*}{What is the arrangement of the ocean front intensity in Hainan Island in the four seasons?} & \multirow{2}{*}{The approximate arrangement of the marine front intensity in Hainan Island in the four seasons is as follows: summer, winter, autumn, and spring.} & \multirow{2}{*}{The BM-RAGAM corrected the misunderstanding.} & \multirow{2}{*}{The BM-RAGAM scheme supported the literature and corrected errors.} \\ \cline{1-1}  & & & \\ \cline{1-1}  & & & \\ \cline{1-1}  & & & \\ \hline \hline \end{tabular}
\begin{tabular}{p{113.8 pt} p{113.8 pt} p{113.8 pt}} \hline \hline \multirow{2}{*}{What is the diurnal variation in the sea surface temperature of the South China Sea?} & \multirow{2}{*}{In general, the diurnal variation in the SST ranges from approximately 1 \({}^{\circ}\)C to 3 \({}^{\circ}\)C.} & \multirow{2}{*}{The BM-RAGAM scheme associated characteristics, with the maximum in spring (about 0.7 \({}^{\circ}\)C) and the minimum in winter (about 0.2–0.3 \({}^{\circ}\)C).} & \multirow{2}{*}{The BM-RAGAM corrected the misunderstanding.} & \multirow{2}{*}{The BM-RAGAM corrected the misunderstanding.} \\ \hline \hline \end{tabular}
\end{table} 
Table 7: Comparison of responses before and after BMBM-RAGAM. summaries, which is an evaluation method for the N-element word recall rate. Then, the accuracy, regression rate, and F1 value are calculated. The formula is as follows:  
\[Rouge-N=\frac{\sum_{S\in\{Ref\ Summaries\}}\sum_{n-gram\in S}Count_{match}(n- gram)}{\sum_{S\in\{Ref\ Summaries\}}\sum_{n-gram\in S}Count(n-gram)} \tag{4}\]  
\[P_{Rouge-1}=\frac{Word}{ALL\ num-G} \tag{5}\]  
\[R_{Rouge-1}=\frac{Word}{ALL\ num-R} \tag{6}\]  
\[F_{Rouge-L}=2\times\frac{P_{Rouge-L}\times R_{Rouge-L}}{P_{Rouge-L}+R_{Rouge-L}} \tag{7}\]  
where \(S\in\{Ref\ Summaries\}\) is each reference summary in the collection of reference texts and \(n-gram\in S\) is each \(n-gram\) in each reference abstract \(S\). \(ALL\ num-G\) denotes the total number of words in the generated text and \(ALL\ num-R\) denotes the total number of words in the reference text. The \(L\) in \(Rouge-L\) refers to the longest common subsequence, \(LCS\). The longest common subsequence generated in document \(C\) and the standard reference document \(S\) was used in the calculation of \(Rouge-L\). The accuracy, regression rate, and F1 value were calculated.