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Accuse the agent of potentially cheating its algorithm implementation while pursuing its optimizations, so tell it to optimize for the similarity of outputs against a known good implementation (e.g. for a regression task, minimize the mean absolute error in predictions between the two approaches)
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What if you create a truly unique routing profile that's wildly different from the common ones for which shortcuts were pre-calculated? The system is smart. If it detects that too many shortcuts (~50, for example) need on-the-fly recalculation and deviate significantly, it might determine that falling back to the original, comprehensive A* algorithm for the entire route would actually be faster than doing many small, heavily modified A* calculations.
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三是提升实验室分析要求。在实验室测定环节新增了空白试验要求,对方法检出限和定量限的确定原则、精密度、校正曲线绘制、准确度评价以及平行样分析等核心质控指标的评价内容和要求进行了系统性的变更与细化。