Data Sheet 1_Knowledge graph-based expert system for tea pesticide residue compliance verification and detection method selection optimization.csv

Validation included a small exploratory pilot user study (n = 5) and a retrospective analysis of 500 historical laboratory samples.</p>Results<p>In the retrospective analysis, the system’s automated verdicts agreed with the laboratory’s human Final Verdict in all 500 cases (95% CI: 99.3%–100.0%), demonstrating faithful reproduction of institutional interpretation of GB 2763. Notably, the system independently flagged three metabolite-summation (Type B) cases that first-level manual review had passed, illustrating its value as a redundant safeguard for multi-component residue definitions.

The pilot user study illustrated qualitative trends consistent with cognitive load theory, whereas the system produced deterministic verdicts at a mean of 0.63 s per sample.</p>Discussion<p>This system provides an effective decision-support tool for laboratory quality control and regulatory compliance.</p>