Release 4.0

• Changed project name to ACKnowledge and added new design
• Improved submission form with additional fields and better descriptions

Version 3.0

This version introduces several improvements, including:

• Improved accuracy of entity extraction
• Simplified data entry and updated instructions for data submission
• Created a link to the 'WormBase AFP Webinar' video
• Updated the FAQs
• Completely switched to wbtools for text mining and DB related functions

Neural Network document classification

We swapped SVM document classifiers with the new NN classifiers developed at WormBase. The new classifiers have higher accuracy compared to the old SVMs. This change is completely transparent to authors and only affects the backend and the APIs that the feedback form uses to read info about a specific paper from caltech's servers (tazendra and mangolassi).

Version 2.0

We improved the AFP system based on feedback received from authors and statistics
collected during one year of AFP v1.0 author submissions. We improved the definition of
data types in the form and we refined our text mining algorithms to obtain better results.

Main Features:

Implemented TFIDF in place of simple thresholds to improve precision of gene and allele recognition
Improved datatype descriptions in "?" mouse-overs
Added FAQs and Release Notes

WormBase AFP system version 1.0

This is the first release of the new Author First Pass system. It includes:

• backend software to process papers from WormBase, extract biological entities, and email authors asking them to validate the extracted data
• automated reminder emails for authors and alerts for curators on new author submissions for their datatypes
• feedback form for authors through which they can send feedback on extracted data and send final submission to WB
• dashboard for curators to monitor AFP submissions and to 'diff' extracted vs. submitted data