In the hit Marvel cinematic universe movie Doctor Strange (2016), talented Neurosurgeon Doctor Stephen Strange suffers a tragic car accident which ruins his medical career. After finding and joining a group of witches and sorcerers, he learns that Kamar-Taj, the group's compound, is under attack. A former member turned rogue named Kaecilius is the attacker. He confronts Doctor Strange on a long stairway. When Kaecilius says "How long have you been at Kamar-Taj, Mister ...," Strange answers with his formal title, "Doctor." A confused Kaecilius replies with "Mister Doctor," and Strange quips back: "It's Strange." Still confused, Kaecilius replies with "Maybe, but who am I to judge." In this brief exchange, Doctor Strange's simple responses cause confusion over his name, and this lack of clarity demonstrates a well below-average example of the Readability attribute.
In the hit TV show Westworld (2016–2022), Dolores has a plan for getting what she wants. As the first self-aware AI host in the park, she knows how to control the action and convince others to do her bidding.
In Season 7, Episode 6 ("Beyond the Wall") of the hit HBO show Game of Thrones (2017), a battle rages between Jon Snow's group and the White Walkers, led by the Night King. As the dragon Viserion is flying around, the Night King is handed a spear by one of his own soldiers. The Night King then aims at the dragon and strikes it, taking the beast down. Later, the Night King walks up to the line separating the two camps and makes eye contact with Snow as he raises his arms. The Night King never speaks or makes any sounds, thus giving no verbal information to anyone, and this demonstrates an extreme-low example of the Volubility attribute.
It’s time to go beyond legacy methods of detecting plagiarism or AI-generated content. The Linguistic Fingerprint™ by LINGA is a revolutionary language analysis technology that sits at the intersection of linguistics, psychology, and computer science. It’s an entirely new way of identifying a person in the form-factors of speech and writing. Linguistic self-discovery awaits.
Venice Beach, CA based DrinkSip makes ultra premium non-alcoholic beer that's always fresh, has lower calories, and tastes delicious. With the DrinkSip Refresher series, you are guaranteed to enjoy great-tasting beer in flavors like watermelon and lime – and there's no hangover so you always Wake Up Happy™.
An ultra low attribute score is exceptionally rare because it represents 5% of the entire population. In a room with 100 other people, a person with an ultra low attribute score would be lower than 95 of them and higher than none of them.
Note: Feels uses a 9-point scoring scale that ranges from Ultra Low to Ultra High according to a normal distribution. See our methodology.
Very Low
5–10% percentile
A very low attribute score is rare because it represents 5% of the entire population. In a room with 100 other people, a person with a very low attribute score would be higher than five of them and lower than 90 of them.
Note: Feels uses a 9-point scoring scale that ranges from Ultra Low to Ultra High according to a normal distribution. See our methodology.
Low
10–20% percentile
A low attribute score is somewhat uncommon and represents 10% of the entire population. In a room with 100 other people, a person with a low attribute score would be higher than ten of them and lower than 80 of them.
Note: Feels uses a 9-point scoring scale that ranges from Ultra Low to Ultra High according to a normal distribution. See our methodology.
Slightly Low
20–40% percentile
A slightly low attribute score is common and represents 20% of the entire population. In a room with 100 other people, a person with a slightly low attribute score would be higher than 20 of them and lower than 60 of them.
Note: Feels uses a 9-point scoring scale that ranges from Ultra Low to Ultra High according to a normal distribution. See our methodology.
Average
40–60% percentile
An average attribute score is typical and represents 20% of the entire population. In a room with 100 other people, a person with an average attribute score would be higher than 40 of them and lower than 40 of them.
Note: Feels uses a 9-point scoring scale that ranges from Ultra Low to Ultra High according to a normal distribution. See our methodology.
Slightly High
60–80% percentile
A slightly high attribute score is common and represents 20% of the entire population. In a room with 100 other people, a person with a slightly high attribute score would be higher than 60 of them and lower than 20 of them.
Note: Feels uses a 9-point scoring scale that ranges from Ultra Low to Ultra High according to a normal distribution. See our methodology.
High
80–90% percentile
A high attribute score is somewhat uncommon and represents 10% of the entire population. In a room with 100 other people, a person with a high attribute score would be higher than 80 of them and lower than 10 of them.
Note: Feels uses a 9-point scoring scale that ranges from Ultra Low to Ultra High according to a normal distribution. See our methodology.
Very High
90–95% percentile
A very high attribute score is rare because it represents 5% of the entire population. In a room with 100 other people, a person with a very high attribute score would be higher than 90 of them and lower than five of them.
Note: Feels uses a 9-point scoring scale that ranges from Ultra Low to Ultra High according to a normal distribution. See our methodology.
Ultra High
95–100% percentile
An ultra high attribute score is exceptionally rare because it represents 5% of the entire population. In a room with 100 other people, a person with an ultra high attribute score would be higher than 95 of them and lower than none of them.
Note: Feels uses a 9-point scoring scale that ranges from Ultra Low to Ultra High according to a normal distribution. See our methodology.