User-created datasets using ordinal scales (such as media ratings) have tendencies to drift or 'clump' towards the extremes and fail to be informative as possible, falling prey to ceiling effects and making it difficult to distinguish between the mediocre and truly excellent.
This can be counteracted by rerating the dataset to create a uniform (and hence, informative) distribution of ratings, but such manual rerating is difficult.
This app owe's itself to Gwern'sresorter, which keeps track of comparisons, infers underlying ratings assuming that they are noisy in the ELO-like Bradley-Terry model, and interactively & intelligently queries the user with comparisons of the media with the most uncertain current ratings, and outputting a fully rescaled set of ratings when the user ends the session. Gwern has also done a huge amount of work compiling noisy-sorting literature, to which I sincerely extend my thanks.
Export your data. Save it somewhere to be uploaded.We'll show a slice of this data after you've loaded it as a sanity check.
After you've loaded the data, we'll do pairwise comparisons of albums.