SOURCE-LINKED INTELLIGENCE

Jev for Scientific Decisions: Evaluating Semantic Choices and Their Consequences

arXiv · AI, language, vision and robotics · article · Sep 21, 2026 · UTC

Scientific workflows often require choosing among known relations before a deterministic calculation can proceed. Whether observations share a culture, treatment or reference standard can change the scientific meaning of the resulting count or comparison. We evaluate Jev as a semantic decision component using a harness that follows its documented guidance and assigns arithmetic to code. The study compares twelve model configurations on twenty source-grounded Choices across ten scientific cases, each repeated five times. We measure semantic selections, downstream outputs and final claim labels

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