Numerous research topics rely on an improved cosmic distance scale (e.g., cosmology, gravitational waves), and the NASA/IPAC Extragalactic Database of Distances (NED-D) supports those efforts by tabulating multiple redshift-independent distances for 12,000 galaxies (e.g., Large Magellanic Cloud (LMC) zero-point). Six methods for securing a mean estimate distance (MED) from the data are presented (e.g., indicator and Decision Tree). All six MEDs yield surprisingly consistent distances for the cases examined, including for the key benchmark LMC and M106 galaxies. The results underscore the utility of the NED-D MEDs in bolstering the cosmic distance scale and facilitating the identification of systematic trends.

中文翻译：

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NED-D 中具有多重估计的星系的平均估计距离

许多研究课题依赖于改进的宇宙距离尺度（例如，宇宙学、引力波），并且 NASA/IPAC 河外距离数据库 (NED-D) 通过为 12,000 个星系（例如，大麦哲伦云 (LMC) 零点）。介绍了从数据中获得平均估计距离 (MED) 的六种方法（例如，指标和决策树）。所有六个 MED 对所检查的案例都产生了惊人的一致距离，包括关键基准 LMC 和 M106 星系。结果强调了 NED-D MED 在支持宇宙距离尺度和促进系统趋势识别方面的效用。