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Functional interventions show that strong forecasters use cross-channel information, while their source-reliance rankings agree little with controlled utility or with one another across iTransformer, TimesNet, and a cross-channel TimeMixer.
Predictive Relevance Retrieval (PRR) combines Pearson retrieval with a futuresupervised predictive representation to expand candidate support, then reranks the union using statistical and learned pair relations to show that predictive relevance and forecast utility are empirically distinct objectives.
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