TERA treats predictive quality as a feasibility threshold and then compares admissible spam/phishing models on latency and resource use instead of collapsing all criteria into one score. Results remain dataset-, threat- and hardware-dependent.
Key findings
- TERA treats predictive quality as a feasibility threshold and then compares admissible spam/phishing models on latency and resource use instead of collapsing all criteria into one score. Results remain dataset-, threat- and hardware-dependent.
Why this matters globally
This work adds internationally comparable evidence in Environment and defines questions for replication in other populations or systems. Its global value lies in the evidence and transferable reasoning, not in a single impact score.
Thai researcher contribution
Thailand-linked authors and Walailak University contribute to the research network behind this work. Thai participation is identified from bibliographic affiliations and should be checked against the author list and source article.
Limitations to consider
Performance can fall under dataset shift; external validation, leakage checks, calibration and post-deployment monitoring are needed.