Sample-efficient active learning for materials informatics using integrated posterior variance

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The tee() memory cliff: Stream.share() requires explicit buffer configuration. You choose the highWaterMark and backpressure policy upfront: no more silent unbounded growth when consumers run at different speeds.

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