Figure 1
A view of the web portal section “Declare your level of expertise.”
Figure 2
A view of the web portal section “Identify letters” (note that templates were called letters in the web portal).
Figure 3
A view of the web portal section “Identify recordings.”
Figure 4
A view of the web portal section “Results,” which presents the number of all classifications made in the portal as well as those made by the user themselves and other users who have approved public visibility of their names. The results also show how well the users’ classifications (identifications in the portal) correspond to the classifications of other users of the same recordings given at species level, and, they show a species-specific recognizability, which is the average proportion of unanimous classifications by candidates among all users.
Figure 5
The number of daily page views on the web portal over time. Dates and types of advertisements are expressed as point shapes on top of the daily page views.
Figure 6
The numbers of classifications by the participating users arranged in descending order from left to right (black dots) and their accumulation curves (grey squares) for (a) the sets of candidates for templates and (b) the 10-second clips. In total, 203 users contributed to candidate classification (a), whereas 43 users also classified clips (b).
Figure 7
Variation among users in their quality of classifications. The plot shows the relation between users’ accuracy in candidates and clips. For candidates, the accuracy score was calculated as the proportion of candidates for which the user’s classification matched the rounded majority vote of the letter. For clips, the accuracy score was calculated by taking the mean of precision (proportion of user’s all-positive votes that were correct according to the majority vote) and recall score (proportion of user’s positive classifications among all species that were present in the recordings). The self-evaluation of the user’s expertise is indicated by the symbol type, and the size of the symbol indicates the number of classifications made by the user (varied from 409 to 31,895 including both candidates and clips).