A layer of rules with soft measurements for agent-based study of magnetic moment flip in an anomalous φ₀-Josephson junction

The paper considers a rule-base layer for agent-assisted investigation of magnetic-moment reversal in an anomalous φ₀ Josephson junction. Literature evidence, expert hints and control simulations are converted into executable rules for scan-parameter selection. Rule ranking uses soft measurements of source confidence, mechanism support, digest alignment, condition specificity, conflict penalty and contribution to the selected parameter family. The control build contains 194 raw records, 48 relevant candidates, 40 executable rules, 367 rule-output/provenance rows, 284 indexed records and 160 trajectory simulations with a reversal fraction of 0.1875. Traceability, conflict and explanation-sparsity metrics are reported. The results show that the rule layer reduces the number of exact solver runs compared with simple parameter-selection baselines while preserving an auditable “rule - contribution - source” link.