This is my attempt at verifying JikkyLeaks count of patients in the Pfizer trial who were N-antibody NEGATIVE at Week_1, then POSITIVE at Week_3.
He claimed that the court ordered data showed that Pfizer's claims of 98% efficacy were likely bogus. There was a much reduced difference between Placebo/Vaccinated when looking at N-antibody data contained in the court ordered Pfizer documents.
You'll need poetry and pandas. With poetry, just type 'poetry shell' then 'poetry install' You'll need to be able to have Jupyter or Vscode use the new poetry python environment
Alternatively, if you don't have poetry you can make it work with pip because pandas is the only dependency. Just create an environment, install pandas, and run Jupyter with that environment.
Download the CSV data as it was originally posted by Jikky. This is because Github won't let me upload the CSV here as its too large. Download it directly from JikkyLeaks source then add it to your environment root. Rename it to remove the messy .zip extension so you just have a neat .csv https://files.catbox.moe/i544mb.zip
Use the file "negative_to_positive_jikky.ipynb" to see for yourself.
The jupyter notebook called "negative_to_positive_pfizer.ipynb" takes the original .xpt file from icandecide and verifies JikkyLeaks original claim.
The advantage of this is it shows that direct from the court ordered data, we can get the same result.
https://www.icandecide.org/pfizer-documents/ https://phmpt.org/pfizers-documents/
The file we're using for this is linked directly here https://www.icandecide.org/wp-content/uploads/2022/05/FDA-CBER-2021-5683-0123168%20to%20-0126026_125742_S1_M5_c4591001-A-D-adva.zip
Alternatively, direct link via phmpt.org https://pdata0916.s3.us-east-2.amazonaws.com/pdocs/050222/FDA-CBER-2021-5683-0123168+to+-0126026_125742_S1_M5_c4591001-A-D-adva.zip
The thread (obviously) has now been censored https://twitter.com/Jikkyleaks/status/1529076970486923264