Communications of the ACM
Humans Help Computers Spot Bursts from Space
Astronomer and citizen science proponent Lucy Fortson of the University of Minnesota, Twin Cities, said humans "need less training data for recognizing patterns” than algorithms do.
Credit: South African Radio Astronomy Observatory
Citizen scientists mined radio astronomy data from the ThunderKAT survey to discover new sources of sporadic space emissions that computer algorithms missed.
A thousand volunteers spent three months sifting through two years of data collected by MeerKAT radio telescopes in South Africa to find new transient sources.
The volunteers evaluated candidates on the citizen science platform Zooniverse by studying images and ascertaining if the central source was a point source, then viewing the corresponding light curve to assess the significance of its variability.
They validated 168 sources already flagged as transient by ThunderKAT's algorithms, and found another 142 that had been overlooked.
From Physics Magazine
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