Comparison of the selected test set analysis results obtained based on expert knowledge and the original AI algorithm

The database is organized as a two-dimensional table that facilitates the comparison of analysis results obtained from three human experts and the AI algorithm. Each row in the table corresponds to a single event and contains several fields. The first field is the event number, which serves as a unique identifier for each record. The second field specifies the event type, categorized as either "A" for workplace accidents or "NM" for near misses. The subsequent fields include the assessments provided by the three experts—Expert 1, Expert 2, and Expert 3—who evaluated and classified each event based on their domain knowledge. Additionally, the table includes a field that assigns the identified causes of each event, providing detailed information about the factors contributing to the occurrence. The final field contains the result generated by the AI algorithm, including its classification and identified causes. This structure enables a comprehensive comparison between expert evaluations and the AI algorithm's output, allowing for the identification of consistencies and discrepancies in both classification and root cause analysis. The database serves as a robust foundation for analyzing the reliability and performance of the AI algorithm in relation to human expertise.