Purpose It’s a training set for resonance-based language modeling. Where ordinary sentiment data rates “positive/negative,” this one rates coherence vs noise—how much a short text expresses clarity, compassion, or awareness rather than confusion or manipulation. It lets a model learn to amplify clear signals and down-weight incoherent ones—the practical job of a Signal Curator. Structure…