I tried feeding a random CNN news I found [1], with the first few paragraph as follows: "London (CNN)The interminable US process for picking a President has it

I tried feeding a random CNN news I found [1], with the first few paragraph as follows: "London (CNN)The interminable US process for picking a President has its faults but as a democratic exercise it outshines the closed-door system being used in Britain to choose a new prime minister. Theresa May resigned as Conservative leader last week after an ill-starred premiership and triggered a party leadership race that will select the next resident of 10 Downing Street by late July." as I added more paragraphs it started to shift from "quite sure this was written by a machine." to "quite sure this was written by a human.". Does this mean the model has learned to take advantage of short text being generated by machine while longer are human written text. A similar effect can be replicate from this article as well[2] [1] https://edition.cnn.com/2019/06/09/politics/uk-prime-minister-race-us-president/index.html?utm_source=feedburner&utm_medium=feed&utm_campaign=Feed%3A+rss%2Fcnn_latest+%28RSS%3A+CNN+-+Most+Recent%29 https://edition.cnn.com/2019/06/09/politics/uk-prime-ministe... [2] https://nypost.com/2019/06/08/mexican-troop-deployment-may-halt-guatemalas-thriving-raft-industry/ https://nypost.com/2019/06/08/mexican-troop-deployment-may-h...