3f487e201802541a37366a02ab9337bdf7036cf8d14ac806f4ff3935903a6983  METHOD.md
1a4781add40bd7b45592d85c6efa3a8ed02389a7dc0f11d151d6586b8f2815ab  PROVENANCE.json
fde1043a2654e8d064543f7ab33d5bd90350368c88052855665e55252e00f6a4  README.md
671bccba4948137954f125b1c453c3c8b7da882aac50e39af48396e09c22f816  SOURCES.md
a013937df15a52b062c33b86e4982ea045f2d5be992416be610955be33dafbaf  public-study.json
5df27a730521c0f051a16a395884214200d394d09c42b9d7dd6b183915d404b6  reproduce.py
b76acdaa1e51a0a74b00fc5a480cfbb483ede13a6342becf3e82faadc3600256  requirements.txt
2ddb4c75023dae27ac765f6058695c25d13604b1e641c80ab172d63312519531  source-contract.json
