Document Type: Model
Status: Active Model
Version: v1.0
Authority: Research Brain (Subordinate to MWMS HeadOffice)
Applies To: All platform-sensitive and compliance-sensitive observations made during Research Brain offer and opportunity research
Parent: Research Brain Architecture
Linked Systems:
Research Brain Canon
Research Brain — Offer Evidence Standards
Research Brain — Research Verdict Framework
Research Brain — Research Confidence Scoring Model
Affiliate Brain
Compliance Brain
Finance Brain
MWMS Decision Authority Matrix
Last Reviewed: 2026-03-26
Purpose
This model defines how Research Brain identifies, classifies, and communicates observable platform-risk and compliance-risk signals during opportunity research.
Research Brain does not provide legal approval.
Research Brain does not provide policy approval.
Research Brain identifies observable risk indicators that may affect downstream viability, routing, or caution level.
This model improves:
risk signal consistency
downstream routing clarity
research quality
decision-support usefulness
Research Brain flags risk.
Research Brain does not approve compliance.
Scope
This model applies to research involving:
affiliate offers
landing pages
sales pages
advertorial pages
lead generation pages
product pages
funnels
creatives where visible
offer messaging
proof structures
pricing or promise framing
This model applies to observable risk indicators related to:
platform policy sensitivity
claim sensitivity
trust-risk structure
credibility-risk structure
message-risk structure
This model does not govern:
legal review
policy enforcement
formal compliance approval
advertising account decisions
merchant approval decisions
Those remain outside Research Brain authority.
Core Principle
Risk signals are not verdicts.
Risk signals are observable patterns that may increase downstream caution.
Research Brain must distinguish between:
visible risk indicator
possible platform sensitivity
formal compliance determination
Research Brain may identify signals.
Research Brain may not simulate official judgement.
Risk Classification Purpose
Risk classification exists to help downstream Brains understand whether an opportunity may carry:
message risk
platform sensitivity
claim fragility
trust concerns
escalation need
Risk classification improves decision context.
Risk classification does not replace specialised review.
Platform Risk Categories
Research Brain classifies risk signals into the following categories.
Category 1 — Claim Risk
Applies where the offer uses strong or fragile claims.
Examples:
dramatic result promises
rapid transformation promises
exaggerated certainty language
unrealistic ease claims
extreme performance promises
Claim risk increases when claims appear difficult to substantiate.
Claim risk does not confirm policy violation.
Category 2 — Health / Body / Medical Sensitivity
Applies where the offer references:
health outcomes
body transformation
symptom relief
medical-style language
appearance-based promise structures
Research Brain should identify observable sensitivity.
Research Brain must not provide legal interpretation.
Category 3 — Income / Wealth / Opportunity Sensitivity
Applies where the offer references:
income generation
wealth creation
business success certainty
lifestyle freedom claims
financial transformation language
These environments often require stronger caution.
Research Brain identifies sensitivity signals only.
Category 4 — Trust / Credibility Risk
Applies where the page shows weak trust structure.
Examples:
missing business identity
vague proof
suspicious testimonials
inconsistent credibility presentation
weak disclosure behaviour
unclear entity ownership
Trust-risk signals matter even when platform policy is not obvious.
Category 5 — Proof Fragility Risk
Applies where proof appears weak, exaggerated, untraceable, or structurally unconvincing.
Examples:
generic testimonials
unsourced success stories
unverifiable screenshots
unsupported authority signals
copied-looking trust elements
Proof fragility affects structural confidence.
Category 6 — Targeting Sensitivity Risk
Applies where messaging appears to target:
personal vulnerabilities
sensitive identity characteristics
emotionally fragile states
fear-amplified conditions
highly pressured response states
Research Brain identifies observable sensitivity patterns.
Research Brain does not perform formal targeting policy review.
Category 7 — Funnel Pressure Risk
Applies where funnel structure appears unusually aggressive.
Examples:
extreme urgency cues
heavy scarcity pressure
repeated forced CTA sequencing
manipulative countdown structures
excessive fear-based transition logic
Pressure risk affects interpretation of structural quality.
Category 8 — Offer Transparency Risk
Applies where the offer structure is unclear.
Examples:
unclear billing logic
unclear continuity model
unclear next-step implications
unclear trial mechanics
hidden-feeling price transition cues
Transparency weakness may increase downstream caution.
Risk Severity Levels
Risk signals should be classified using 4 levels.
Low Risk Signal
Minimal visible sensitivity.
Examples:
moderate claims
standard persuasion language
normal pressure structure
clear transparency
Low risk does not mean safe.
Low risk means few obvious signals are visible.
Moderate Risk Signal
Some visible sensitivity or fragility.
Examples:
strong claims with limited support
moderate urgency pressure
partial trust concerns
partial proof fragility
Moderate risk suggests caution awareness.
Elevated Risk Signal
Multiple visible concerns or stronger signal concentration.
Examples:
aggressive claims
fragile proof
unclear offer structure
stronger policy-sensitive wording
repeated urgency pressure
Elevated risk suggests stronger downstream caution.
High Risk Signal
Strong concentration of visible sensitivity indicators.
Examples:
extreme promises
highly fragile proof
aggressive pressure logic
severe transparency weakness
strongly sensitive claim environments
High risk does not equal formal violation.
High risk indicates significant caution signal density.
Risk Identification Dimensions
Research Brain should assess risk across these dimensions:
Claim intensity
Proof reliability
Trust structure
Transparency clarity
Pressure level
Sensitivity domain
Target vulnerability cues
The objective is not legal interpretation.
The objective is structured signal identification.
Risk Signal Interpretation Rule
Research Brain must describe risk signals using measured language.
Avoid:
non-compliant
banned
illegal
policy violation
will be rejected
Unless such status is formally known from authoritative internal context.
Prefer:
shows elevated claim sensitivity
contains visible trust fragility
appears to carry stronger platform-risk signals
uses messaging patterns that may require caution
contains stronger transparency concerns
Risk and Confidence Relationship
High risk visibility does not always reduce structural confidence.
Example:
a page may clearly show risky patterns.
In such cases:
Confidence in the presence of risk signal may be high.
Confidence in commercial viability may remain separate.
Confidence applies to the observation, not to the business outcome.
Relationship to Research Verdict Framework
Risk signals contribute to:
Research Verdict Support
Recommended Next Step
Confidence framing
Risk does not become the whole verdict by itself.
Verdict must consider total evidence picture.
Relationship to Affiliate Brain
Affiliate Brain may use risk classification to decide whether an opportunity deserves:
testing caution
deeper review
creative adaptation caution
further evidence gathering
Research Brain does not decide campaign approval.
Relationship to Compliance Brain
Where a specialist compliance function exists, Research Brain may route opportunities for deeper review.
Research Brain identifies signals.
Compliance authority remains elsewhere.
Relationship to Finance Brain
Risk signals may affect whether an opportunity should progress into deeper economic evaluation.
Research Brain does not determine capital restrictions.
Finance Brain evaluates economics, not messaging compliance.
Observable vs Assumed Risk
Research Brain must only classify visible signals.
Research Brain must not assume:
hidden advertiser policy history
account restrictions
merchant history
backend compliance status
legal review status
Where unknown, unknown must remain unknown.
Output Format Example
Platform Risk Signal:
Elevated Risk Signal
Primary Risk Categories:
Claim Risk
Proof Fragility Risk
Offer Transparency Risk
Risk Notes:
Page uses strong outcome language with limited visible substantiation. Billing structure appears partially unclear. Testimonial style appears structurally weak.
Confidence:
Moderate
Drift Protection
Research Brain must avoid becoming:
a legal review layer
a policy enforcement simulator
a fear amplification layer
an arbitrary blocker
Research Brain must remain:
signal-aware
evidence-aware
measured
bounded by scope
Architectural Intent
The Platform Risk Classification Model ensures Research Brain can identify and communicate risk-sensitive opportunity features consistently without crossing into formal compliance authority.
This improves routing clarity and preserves Research Brain’s analytical role.
Final Rule
Research Brain may identify risk signals.
Research Brain may not simulate formal compliance authority.
Research Brain provides structured caution signals only.
Change Log entry
Add this to Research Brain Change Log:
2026-03-26 — Added Platform Risk Classification Model v1.0
Change Type: Structural Extension
Authority: Research Brain
Scope Impact: Defines structured method for identifying and expressing platform-risk and compliance-risk signals
Parent Architecture Impact: None
Decision Authority Impact: None
Backward Compatibility: Maintained
Summary
Added new model:
Research Brain — Platform Risk Classification Model v1.0
Defines structured categories for claim risk, health/body sensitivity, income sensitivity, trust risk, proof fragility, targeting sensitivity, funnel pressure risk, and offer transparency risk, along with four severity levels.
Reason for Change
Research outputs required consistent handling of visible platform-risk and compliance-risk indicators without drifting into legal or policy authority.
Architectural Intent
Improve consistency of risk-signal communication and preserve Research Brain as an analytical evidence layer rather than a compliance authority.