The parameters of a study on Mabyduck are controlled by two types of objects: experiments and jobs. An experiment decides the type of study, the details of the user interface, and the data to be evaluated. For example, a MUSHRA experiment evaluating a set of compressed audio files. Each experiment can have multiple jobs. These define who the raters are, and how much data each rater will evaluate. This allows you to run the same experiment with different groups of raters, and see how they compare.
The most important concepts of the Mabyduck platform are:
When a rater participates in a study, this creates a session associated with the job. Depending on the configuration of a job, a rater might participate multiple times in a study, creating multiple sessions.
Each session consists of multiple slates that represent a group of stimuli evalauted together. In the simplest case, a slate is associated with a single stimulus that was rated on an absolute category rating scale (e.g., on a scale from 1 to 5). For a MUSHRA experiment, a slate corresponds to the set of audio files that were rated together.