Parent Standard: Transparency & Probabilistic Integrity Standard
Methodology Sign: Fair Win Model™ (FWM™)
Category: Governance & Enforcement
Subcategory: Remaining-State Computation
Type: Probabilistic Integrity Module
Version: 1.0
Status: Canonical · Open Module
Effective Date: 9 May 2026
Compatibility: OOF® Methodology OS™ · Transparency & Probabilistic Integrity Standard · TVL® · INTEGROS® · ArtData® · UCL™
Authority: OOF®
Protection: MIP® — Methodological Intellectual Property
Canonical Language: English (UCL™)

Canonical Definition

Remaining-State Computation Module defines the structural
conditions under which the current remaining prize, reward, or
probabilistic allocation reality of a system is computed from traceable
source events in a reproducible, auditable, and integrity-verifiable
manner.

A system satisfies RSCM only if:

• remaining-state computation is based on traceable source events
• computation logic is reproducible under defined conditions
• the resulting remaining-state output is auditor-verifiable
• computation does not silently distort remaining reality through omission, ambiguity, or hidden transformation
• lifecycle transparency remains structurally linked to actual committed, distributed, and redeemed states

A system that cannot compute remaining-state reality in a reproducible
and reviewable manner does not satisfy RSCM.

Module Function

RSCM defines the computational truth layer of probabilistic
transparency.

It ensures that a probabilistic system does not rely on symbolic,
promotional, or manually asserted claims about what still remains
possible, but on computed remaining-state reality derived from
verifiable lifecycle events.

The module applies wherever operators, auditors, regulators, or market
participants must know the factual current state of what remains
available.

Minimum Implementation Framework (MIF)

Step 1 — Define Source Event Classes

The organization must define which source events affect remaining-state
reality.

Minimum requirement:

• relevant lifecycle events are explicit
• commitment, distribution, redemption, invalidation, expiry, or other state-changing events are distinguishable
• undefined source-event logic is excluded from valid computation

Step 2 — Define Computation Logic

The system must define how remaining-state reality is computed from
source events.

Minimum requirement:

• computation logic is explicit
• state change rules are identifiable
• hidden or arbitrary computation transformation is excluded from valid operation

Step 3 — Define Reproducibility Conditions

The system must define how remaining-state outputs can be reproduced.

Minimum requirement:

• reproducibility conditions are explicit
• the same source events yield the same computed state under the same logic
• non-reproducible remaining-state outputs are excluded from valid transparency

Step 4 — Define Verification Conditions

The system must define how computed remaining-state outputs may be
reviewed and verified.

Minimum requirement:

• computed state is auditor-verifiable
• source-event linkage remains reviewable
• unverifiable remaining-state computation is excluded from valid operation

Step 5 — Preserve Computation Integrity

The system must preserve consistency between source events and computed
remaining-state reality.

Minimum requirement:

• computed outputs remain aligned with committed, distributed, and redeemed states
• silent omission or distortion is identifiable
• remaining-state computation remains structurally trustworthy

Step 6 — Restrict Invalid Remaining-State Computation

The system must not be treated as valid if remaining-state reality is
computed through opaque, irreproducible, non-verifiable, or structurally
distorted logic.

Minimum requirement:

• invalid computation conditions are identifiable
• non-traceable or manipulated remaining-state outputs are blocked or invalidated
• numeric output alone does not justify missing computational integrity

Use Case 1 — Lottery Remaining Prize Computation

Scenario

A lottery operator must determine how many prizes remain available at a
given point in lifecycle while ensuring that the result is based on
actual committed, distributed, and redeemed reality.

Application

RSCM is used to ensure:

• source event classes are explicitly defined
• computation logic is reproducible
• remaining-state outputs can be independently reviewed
• the public or regulatory representation of remaining availability is structurally linked to factual lifecycle events

Result

The operator gains a stronger basis for proving that remaining prize
disclosures reflect real computed availability rather than symbolic or
unverified reporting.

Use Case 2 — Digital Reward System with Dynamic Remaining Pool

Scenario

A digital reward platform maintains a changing reward pool across
claims, expiries, invalidations, and completed redemptions, and must
ensure that the current remaining state is materially correct.

Application

RSCM is used to ensure:

• all state-changing events are included in computation
• remaining-state logic is explicit and reproducible
• current reward reality can be verified by audit
• lifecycle transparency remains computationally grounded

Result

The platform gains a structurally governed computation layer instead of
relying on opaque remaining-state assertions.

Canonical Closing Statement

If remaining reality cannot be computed from verifiable source
events, remaining transparency cannot be materially trusted.

→ Transparency & Probabilistic Integrity Standard