Examples
Each example shows how Omega protocols expose structure — not whether the claim is true or false.
These examples show how Omega protocols expose structure in different types of claims. Each example identifies what's claimed, what's assumed, what's shown, what's missing, and alternative framings.
Research Claim
"AI systems trained on large datasets will achieve human-level performance in most cognitive tasks within 5 years."
What it claims
Predicts AI performance reaching human levels in most cognitive tasks within a 5-year timeframe.
What it assumes
- •Large datasets are sufficient for human-level performance
- •Current training methods will scale
- •Cognitive tasks are measurable and comparable
What's actually shown
- •No specific evidence provided
- •No definition of "human-level performance"
- •No specification of which cognitive tasks
What's missing / unclear
- •What datasets are required
- •What training methods
- •How performance is measured
- •What "most" means
Other framings
- •Could be interpreted as net positive (capability) or net negative (displacement)
- •Assumes linear progress rather than plateaus or setbacks
Policy Statement
"This new regulation will reduce emissions by 50% while maintaining economic growth."
What it claims
Regulation will achieve 50% emission reduction without negative economic impact.
What it assumes
- •Regulation is enforceable
- •Economic growth metrics remain unchanged
- •No substitution effects
What's actually shown
- •No specific regulation details
- •No baseline for "50%"
- •No definition of "economic growth"
What's missing / unclear
- •What the regulation requires
- •How compliance is verified
- •What happens to non-compliant actors
- •Timeframe for reduction
Other framings
- •Could prioritize environmental goals over economic ones
- •Could assume economic growth definition excludes externalities
Product Promise
"Our new platform will increase productivity by 3x with zero learning curve."
What it claims
Platform delivers 3x productivity improvement with no user training required.
What it assumes
- •Productivity is measurable and comparable
- •Zero learning curve is achievable
- •Current productivity baseline is known
What's actually shown
- •No definition of productivity
- •No specification of tasks or users
- •No evidence of zero learning curve
What's missing / unclear
- •What productivity means
- •What tasks are included
- •Who the users are
- •How improvement is measured
Other framings
- •Could prioritize ease-of-use over capability
- •Could assume productivity gains are universal
Technical Architecture
"This distributed system design will handle 10x traffic with 50% lower latency."
What it claims
System architecture supports 10x traffic increase with 50% latency reduction.
What it assumes
- •Traffic patterns remain similar
- •Latency is measurable and comparable
- •No bottlenecks emerge at scale
What's actually shown
- •No specific architecture details
- •No baseline traffic or latency
- •No load testing results
What's missing / unclear
- •What the architecture is
- •How traffic is distributed
- •What causes latency
- •How latency is measured
Other framings
- •Could prioritize scale over consistency
- •Could assume latency improvements are uniform
Business Strategy
"Expanding into this new market will double revenue within 18 months."
What it claims
Market expansion will achieve 2x revenue growth in 18-month timeframe.
What it assumes
- •New market is accessible
- •Current revenue model applies
- •No competitive response
What's actually shown
- •No market analysis
- •No revenue model details
- •No competitive assessment
What's missing / unclear
- •What the market is
- •How expansion happens
- •What revenue model
- •What costs are involved
Other framings
- •Could prioritize growth over profitability
- •Could assume market conditions remain favorable
Scientific Finding
"This study demonstrates that treatment X is 80% more effective than standard care."
What it claims
Treatment X shows 80% effectiveness improvement over standard care.
What it assumes
- •Effectiveness is measurable and comparable
- •Study design is valid
- •Results are generalizable
What's actually shown
- •No study methodology
- •No sample size or demographics
- •No definition of effectiveness
What's missing / unclear
- •What the study design was
- •Who the participants were
- •How effectiveness was measured
- •What standard care means
Other framings
- •Could prioritize statistical significance over clinical significance
- •Could assume results apply to all populations