68 research outputs found

    Non-Standard Errors

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    In statistics, samples are drawn from a population in a data-generating process (DGP). Standard errors measure the uncertainty in estimates of population parameters. In science, evidence is generated to test hypotheses in an evidence-generating process (EGP). We claim that EGP variation across researchers adds uncertainty: Non-standard errors (NSEs). We study NSEs by letting 164 teams test the same hypotheses on the same data. NSEs turn out to be sizable, but smaller for better reproducible or higher rated research. Adding peer-review stages reduces NSEs. We further find that this type of uncertainty is underestimated by participants

    Transfer of mouse anti-xenotropic virus neutralizing factor to human lipoproteins.

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    We examined the migratory properties of the mouse serum protein responsible for specific neutralization of the endogenous mouse xenotropic type C virus and demonstrated that this neutralizing factor can be transferred from mouse lipoproteins to human and to nonreactive mouse lipoproteins. After acceptance of this activity by these lipoproteins, it could be back-transferred to human and to mouse lipoproteins. This result was compatible with equilibrium binding of the responsible proteins by several classes of lipoproteins. The best expression of the transferred activity occurred with human chylomicrons. Small quantities of neutralizing factor which exist in free dispersion in serum were also detected by mixing the p greater than 1.21 g/ml density fraction of mouse serum with human chylomicrons; antiviral activity was subsequently found associated with the human lipoproteins. This result reflects the potentiation of antiviral activity of the protein in a lipoprotein environment. These observations offer a useful approach for the eventual purification and characterization of the neutralizing factor

    Googling Gold and Mining Bad News

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