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Auxology has developed from mere describing child and adolescent growth into a vivid and interdisciplinary research area encompassing human biologists, physicians, social scientists, economists and biostatisticians. The meeting illustrated the diversity in auxology, with the various social, medical, biological and biostatistical aspects in studies on child growth and development.
We analyze the light curve of the microlensing event OGLE-2003-BLG-175/MOA-2003-BLG-45 and show that it has two properties that, when combined with future high-resolution astrometry, could lead to a direct, accurate measurement of the lens mass. First, the light curve shows clear signs of distortion due to the Earth's accelerated motion, which yields a measurement of the projected Einstein radius (r) over tilde (E). Second, from precise astrometric measurements, we show that the blended light in the event is coincident with the microlensed source to within about 15 mas. This argues strongly that this blended light is the lens and hence opens the possibility of directly measuring the lens- source relative proper motion mu(rel) and so the mass M=(c(2)/4G)mu(rel)t(E)(r) over tilde (E), where t(E) is the measured Einstein timescale. While the light-curve-based measurement of (r) over tildeE is, by itself, severely degenerate, we show that this degeneracy can be completely resolved by measuring the direction of proper motion mu(rel)
This study pushes our understanding of research reliability by reproducing and replicating claims from 110 papers in leading economic and political science journals. The analysis involves computational reproducibility checks and robustness assessments. It reveals several patterns. First, we uncover a high rate of fully computationally reproducible results (over 85%). Second, excluding minor issues like missing packages or broken pathways, we uncover coding errors for about 25% of studies, with some studies containing multiple errors. Third, we test the robustness of the results to 5,511 re-analyses. We find a robustness reproducibility of about 70%. Robustness reproducibility rates are relatively higher for re-analyses that introduce new data and lower for re-analyses that change the sample or the definition of the dependent variable. Fourth, 52% of re-analysis effect size estimates are smaller than the original published estimates and the average statistical significance of a re-analysis is 77% of the original. Lastly, we rely on six teams of researchers working independently to answer eight additional research questions on the determinants of robustness reproducibility. Most teams find a negative relationship between replicators' experience and reproducibility, while finding no relationship between reproducibility and the provision of intermediate or even raw data combined with the necessary cleaning codes.