The phrase "attractiveness level" is correct and usable in written English.
It can be used to describe the degree or extent of attractiveness of a person, object, or concept in various contexts, such as marketing, psychology, or personal opinion.
Example: "The study aimed to measure the attractiveness level of different advertising campaigns to determine which was most effective."
Alternatives: "degree of attractiveness" or "attractiveness rating".
The licensing schema is indeed associated with variations attractiveness level, not in all, but in many cases, having a meaningful effect size in a few of them.
In deterministic utility model, the customers visit the facility with the highest utility, whereas in random utility they visit each facility by a certain probability that is directly related to the attractiveness level of the facility and inversely related to the attractiveness level of all the existing facilities.
Hily works by employing matchmaking algorithms which are based on machine learning instead of the geographical location of a user or "attractiveness level" (as used by Tinder) which might keep you swiping in the app but actually reduces your chances as around 80% of people are rejected.
The overall attractiveness level of the dish groups compared was not controlled for, and could have been higher for one of the groups.
For the content, aspects such as attractiveness, level of difficulty, and use of material were measured.
Wearing long lasting eye shadow or clothes to match the setting you are in may just help boost your attractiveness level.
An 80s study at the University of Maryland compared attractiveness levels in 123 couples (on a nine-point scale) and gave them a 35-page relationship questionnaire (they may have been fishing for many different hypotheses, because they asked so many questions that would make the findings more likely to be coincidental).
Hily ignores attractiveness levels and goes for better matches, identifying users with the same interests and a higher probability of matching, taking data from the depth of dialogue, mutual likes, photos sent etc.
Using event-related fMRI, we were able to present single items rather than blocked groups, allowing 'mixing' of different attractiveness levels.
The aim of this search was to single out items whose attractiveness levels are particularly susceptible to increased (or decreased) hunger, and identify the neural activation that characterizes them.
Our results point to the representation of food value in the amygdala, and to an integration of attractiveness with hunger level in the orbitofrontal cortex.
