Historical Anchors for Scientific Forecasting on Human-Aware Knowledge Graphs
The paper introduces Query-Anchor Agreement (QAA), a diagnostic tool to determine if a learned representation of scientific knowledge has stabilized enough for reliable forecasting. QAA compares predictions based on the target concept versus those based on historical examples, identifying when these views converge and signaling a target-relevant sampling regime without needing future labels.