Comment by quuxplusone

Ryuta Kinugasa, Yoshiyuki Usami. "How Fast Can a Human Run? Bipedal vs. Quadrupedal Running." Frontiers of Bioengineering and Biotechnology 4:56 (June 2016).

That looks remarkably like an April Fool's article released at the wrong time of year. The second-to-last paragraph is where they reveal the joke to anyone who wasn't already in on it:

> This study has limitations. Although statistical models are significantly related to mathematical formula [sic], the use of a statistical model to accurately predict future athletic performance is challenging (Hilbe, 2008). Fitted linear models should be treated with some caution. The use of linear regression for world record modeling would yield a continued decline that would eventually become negative, thus suggesting that update of world records can be continued until 0 s. It must also be noted that quadrupedal world records did not exist before 2008. This relatively recent involvement [sic] of quadrupedal running results in a somewhat tenuous comparison of world record times. Therefore, despite a high coefficient of determination, a large diverging confidence interval was found.—

—and then right back into it—

> —The 95% confidence intervals [sic] indicates that projected intersects could occur as early as in 2032 (9.238 s) or as late as 2076 (9.341 s).

A "rebuttal paper" might accept their major premise (i.e. feasibility of "a statistical model to accurately predict future athletic performance") but argue that rather than fitting a straight line (linear regression), we should fit an exponential decay curve (exponential regression). In an appendix, we'd try fitting a hyperbola (y = K1/(x-X0) + K2), taking X0 for quadrupedal running at 2008 and X0 for bipedal running anywhere from 2 million to 10 million years ago.

In an alternative "experimentalist approach," the rebuttal paper's author would actually run 100m himself, first on two legs and then on four; plot these as an additional data point (with x=2025) in each set; and fit a polynomial to that data. This would likely change the conclusion quite drastically. ;)