Processes performance data to assert causal pathway attributes about performers.
Functions to process input data and determine if attribute is present or not.
Each function is called with the performance data and a column spec as args.
It is expected to return a table of the id and boolean value of the attribute.
Returned table must be grouped by id. e.g the result of annotate_capability_barier:
| id | cabability_barrier |
|---|---|
| Alice | TRUE |
| Bob | FALSE |
| Carol | FALSE |
JSON-LD description of project including any apriori assertions about performers.
CSV format of performer, timepoint, value
Situation specific interpretation of the performance values.
Specified by collaborator or domain expert.
Distilled down to statements that can be implemented by an algorithm,
and subsequently written as functions in an annotations.r file.
Annotate each performer with applicable attributes:
-
capability_barrier
Score above 10 for at least 3 consecutive time points or Score above 15 at any point -
performance_gap_pos
Value above %110 of background average at last time point. -
performance_gap_neg
Performance below %90 of background average at last time point.