# Sys1Cal-v1

Porcedda built Sys1Cal-v1, a synthetic dataset of 365 True/False items derived from 92 probability problems whose proposition probabilities are known by construction, and used total variation distance and distributional overlap (soft accuracy) to evaluate Jev's Noul, Choice, and Score primitives plus the open-source baseline SemIf, finding that Jev's Choice probabilities are systematically distorted and that inverting a latent third truth value of uncertainty estimated from Score expectations raises median Choice soft accuracy from 0.771 to 0.978.

Porcedda built Sys1Cal-v1, a synthetic dataset of 365 True/False items derived from 92 probability problems whose proposition probabilities are known by construction, and used total variation distance and distributional overlap (soft accuracy) to evaluate Jev's Noul, Choice, and Score primitives plus the open-source baseline SemIf, finding that Jev's Choice probabilities are systematically distorted and that inverting a latent third truth value of uncertainty estimated from Score expectations raises median Choice soft accuracy from 0.771 to 0.978.