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Extraordinary claims require extraordinary evidence. That truism, now known as the "Sagan standard" after science communicator Carl Sagan, has been around in some form since David Hume first published it in the 1740s. But, with modern-day data collection, sometimes even extraordinary evidence isn't enough鈥攊t's how you interpret it.

That's the argument behind a new paper on the arXiv preprint server by Luis Welbanks and their colleagues at Arizona State University and various other American institutions. They analyzed the data behind the recent claims of biosignature detection in the atmosphere of K2-18b and found that other non-biological interpretations could also explain the data.

We previously reported on the detection of dimethyl sulfide (DMS) in the atmosphere of K2-18b, a sub-Neptunian exoplanet orbiting a star about 124 light-years away in the constellation Leo. The finding was initially reported in September 2023, with more recent data from April seeming to back up the claim.

However, we've also reported plenty of other explanations for that signal, including explanations of the signal's non-biological creation and overarching discussions about whether the James Webb Space Telescope (JWST), which first collected the data, could even detect life on other planets. Obviously, claims such as finding life on an exoplanet will garner a lot of skeptics, and this new paper continues in that tradition.

It takes a more statistical approach to its criticism, though. It rightly claims that detecting individual chemicals in the atmosphere is hard. Doing so with the limited data that even instruments like JWST can provide requires comparing potential models of the atmosphere to the data and seeing which one best represents it.

Unfortunately, this requires a lot of statistical guessing. To simplify the process, astronomers typically eliminate entire classes of models to conform to "Occam's Razor"鈥攖he philosophical principle that the simplest explanation is the most likely. To do so, they use the Bayesian model comparison technique, which compares the relative fit of two separate models to the data and selects the one that fits better as the more likely scenario.

This practice leads to two problems. First, if all the models are poor representations of reality, the one that comes out on top of the Bayesian analysis is simply the "least inadequate" one. That doesn't engender much confidence in the model's accuracy. On the other hand, if multiple models fit the data well, even if one fits better, it doesn't necessarily mean that the others are inaccurate.

To prove their point, the authors reanalyzed the dataset used in the original biosignature detection paper through multiple other models that were discarded as part of that paper. They found good fits for models that abiological processes could entirely explain. One particular model that included the hydrocarbon propyne (C₃H₄) fit the data better than the model containing DMS and its cousin, dimethyl disulfide (DMDS), which was described in the paper in April.

The ongoing scientific debate around the interpretation of the data is warranted. After all, claiming to have found signs of life on an alien planet would mark it as one of the biggest discoveries in human history.

One of the best things about the scientific method is how it handles disagreements like this one鈥攎ore data is needed to address the concerns in the recent pre-print and the other papers we've been reporting on.

And as scientists collect that data, even if it takes another generational advance in space telescopes, we'll get closer to understanding the truth of the composition of K2-18b's atmosphere鈥攁nd maybe whether we're not alone in the universe after all.