Falsification Python Packages

gnosis-morph-bench

Benchmark-first methods lane for Gnosis extraction in the Zer0pa portfolio: neutral route scoring, null metrics, stability battery, deterministic replay. Methodology surface; useful now, improving continuously.

cuneiform-control

Negative-control / no-go preservation lane in the Zer0pa Gnosis Portfolio. Manifest-validation smoke + failed-gate evidence chain. Methodology only; no decipherment claim. Useful now, improving continuously.

gnosis-indus

Indus-script anchor application in the Zer0pa Gnosis Portfolio: clean-room search-without-decode runtime + Phase 4 conditional catalogue at k=70 + Phase 5 non-decipherment posture. No decipherment claimed. Useful now, improving continuously.

zpe-video

Perception receipts for AI video pipelines. Cross-writer bit-exact under default settings (SHA-256 stable across writers in any language). Zero runtime dependencies; pure stdlib core. ~1.1 KB per video; per-frame CRC32 + schema + versioning. Useful now, improving continuously.

zer0pa-materials-workbench

CPU-verified in silico materials research control plane. Battery + thermoelectric pipeline staged for H100 GPU evidence campaign. Research infrastructure, not a discovery engine.

zpe-dm3

Deterministic computation substrate diagnostic — Zer0pa Computation portfolio. 380v C3-symmetric graph (P_95 □ K_4); ARM64 cross-platform determinism (claim τ); trimodal sawtooth + s50 cliff confirmed for shape; static reconstruction at Tier-2 (R8 OPEN).

zpe-taste

Evidenced-negative taste object — failed the geometry-bearing fit gate (metric_fit 0.207 vs 0.6 threshold). The committed negative reference is preserved as the lab record. No positive taste codec is claimed.

causal-falsify

causal-falsify: A Python library with algorithms for falsifying the unconfoundedness assumption in a composite dataset from multiple sources.

falsifyai

Falsification-first reliability testing for AI systems: perturb inputs, preserve replayable evidence, diff reliability across model changes.