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Garbage in, garbage out
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==Uses== This phrase can be used as an explanation for the poor quality of a digitized audio or video file. Although [[digitizing]] can be the first step in cleaning up a signal, it does not, by itself, improve the quality. Defects in the original analog signal will be faithfully recorded, but might be identified and removed by a subsequent step by [[digital signal processing]]. GIGO is also used to describe failures in human [[decision-making]] due to faulty, incomplete, or imprecise data.<ref>{{FOLDOC|Garbage+in%2C+garbage+out}}</ref> In [[audiology]], GIGO describes the process that occurs at the [[dorsal cochlear nucleus]] (DCN) when [[auditory neuropathy spectrum disorder]] is present. This occurs when the neural firing from the cochlea has become unsynchronized, resulting in a static-filled sound being input into the DCN and then passed up the chain to the auditory cortex.<ref>Berlin, Hood, Russell, Morlet et al (2010) [http://csd.cbcs.usf.edu/an/Berlin_ANSD.pdf Multi-site diagnosis and management of 260 patients with Auditory Neuropathy-Dys-synchrony (Auditory Neuropathy Spectrum Disorder)]</ref> The term was applied by Dan Schwartz at the 2012 Worldwide ANSD Conference, St. Petersburg, Florida, on 16 March 2012; and adopted as industry jargon to describe the electrical signal received by the [[dorsal cochlear nucleus]] and passed up the auditory chain to the [[superior olivary complex]] on the way to the [[auditory cortex]] destination.{{fact|date=February 2023}} GIGO was the name of a [[Usenet]] gateway program to [[FidoNet]], MAUSnet, e.a.<ref>{{cite web |url=http://gigo.com/wiki/GIGO_History|title=GIGO History|author=jfesler|date=2001-01-01|website=gigo.com|access-date=2014-01-24}}</ref> The phrase may also be used in the context of [[machine learning]], where poor-quality training data will inevitably lead to a poor-quality model.
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