  This paper calibrates how metrics derivable from the SAO/NASA Astrophysics
Data System can be used to estimate the future impact of astronomy research
careers and thereby to inform decisions on resource allocation such as job
hires and tenure decisions. Three metrics are used, citations of refereed
papers, citations of all publications normalized by the numbers of co-authors,
and citations of all first-author papers. Each is individually calibrated as an
impact predictor in the book Kormendy (2020), "Metrics of Research Impact in
Astronomy" (Astron Soc Pac Conference Series Monograph 8, San Francisco). How
this is done is reviewed in the first half of this paper. Then, I show that
averaging results from three metrics produces more accurate predictions.
Average prediction machines are constructed for different cohorts of 1990-2007
PhDs and used to postdict 2017 impact from metrics measured 10, 12, and 15
years after the PhD. The time span over which prediction is made ranges from 0
years for 2007 PhDs to 17 years for 1990 PhDs using metrics measured 10 years
after the PhD. Calibration is based on perceived 2017 impact as voted by 22
experienced astronomers for 510 faculty members at 17 highly-ranked university
astronomy departments world-wide. Prediction machinery reproduces voted impact
estimates with an RMS uncertainty of 1/8 of the dynamic range for people in the
study sample. The aim of this work is to lend some of the rigor that is
normally used in scientific research to the difficult and subjective job of
judging people's careers.
