Knowledge<T> as a Primitive
Values carry uncertainty, confidence, and provenance by default instead of external spreadsheet logic.
Sounio treats scientific trust as a language concern. The type system keeps uncertainty, provenance, and effect boundaries visible from first line to production deployment.
Mechanisms that make trust and performance coexist in one systems language.
Values carry uncertainty, confidence, and provenance by default instead of external spreadsheet logic.
Control flow can branch on confidence guarantees, so runtime behavior reflects evidence quality.
I/O, mutation, allocation, GPU, and probabilistic effects are visible in function signatures.
Dimensions and refinement checks make invalid scientific operations fail before deployment.
Every value evolves through four tiers — from bare numeric to a fully epistemic, provenance-tracked type.
Raw scalar or structured value with no attached evidence metadata.
Value promoted to dimension-aware representation with unit constraints.
Uncertainty, confidence, and source attribution become part of the value.
Executable value with traceability chain for audit and reproducibility.
Trust conditions become explicit runtime behavior rather than hidden assumptions.
let concentration: Knowledge<mg_per_l> = measure(
value: 9.8,
uncertainty: 0.3,
confidence: 0.97,
source: "lab_run_042"
)
if concentration.confidence > 0.95 {
approve_for_decision(concentration)
} else {
request_remeasurement(concentration)
} Uncertainty propagates automatically through every operation. Confidence gates enforce data quality at the call site — no boilerplate.
Capture value + uncertainty + confidence from instrument or model.
Composition rules carry uncertainty through transformations.
Confidence thresholds and effect policies decide admissibility.
Execution continues only when evidence satisfies gate criteria.