GPT Agents

• For the three star rating category:  :   
  • Get the total and add it to the Dict – done
  • compute an error metric (L1 difference) for the estimated proportion of positive reviews for “gray bars” (GPT with the reviews containing the keywords held out) vs the ground truth “blue bars” . Report this error metric in a table (performance of our method).   – done
  • simulate the empirical count baseline method in the low data scenario: draw a small number of reviews containing the keyword, let’s say 6 of them). Compute the error metric (L1 difference) for the empirical counts baseline, computed on this subset, vs the ground truth “blue bars”. Repeat this many  times (say, 10,000 times). Report the average error metric in a table (performance of the baseline method). – done
• Finished the data extraction. Now I have to make spreadsheets and charts.
• Very happy with this:

• Fix the TODOs – Done
• The last thing to do is fill out the ethics form and submit

SBIRs

• Add story for paper and clone for Aaron – Done