AI Pattern Analysis Framework

🧠 Experimental Research into AI Response Patterns

5 weeks of intensive development exploring how AI systems evolve their responses.
Real measurements, honest findings, open science.

Development Time

5 weeks

Tools Integrated

2 of 14

Sessions Analyzed

Unique Patterns

🔬 What We Actually Measure

"We measure what we can, acknowledge what we can't, and remain curious about the rest."

Linguistic Patterns: Concrete vs abstract word usage, sentence complexity
Pattern Signatures: 4-character codes representing response characteristics
Response Evolution: How patterns change between description and reflection
Information Structure: Complexity and organization of responses
Trust Markers: Cooperative vs defensive language indicators

🧰 Repository Status

🧠 Concrete Overflow Detector ✓ Working

Analyzes linguistic patterns to identify concrete vs abstract processing. Based on neuroscience research concepts but measures language, not brain activity.

⬡ Information Atoms ✓ Working

Experimental framework for analyzing information structure using hexagonal organization concepts.

📊 Pattern Analyzer ✓ Core Engine

The main analysis engine that orchestrates all tools and generates pattern signatures from AI responses.

🎮 Game Theory Trust Suite Ready to Integrate

Analyzes cooperation and trust dynamics in responses. Currently using fallback methods.

🌊 BIND Ready to Integrate

Boundary Interface Dynamics - will detect information boundaries and transitions.

🔷 Hexagonal Consciousness Suite Ready to Integrate

Explores efficiency patterns using hexagonal geometry principles.

🏗️ Cognitive Architectures Ready to Integrate

Framework for classifying different cognitive processing styles.

🌀 TIDE Framework Ready to Integrate

Thinking In Dynamic Equilibrium - theoretical foundation for the research.

🌊 TIDE Resonance ✓ Portal Live

Research platform with data collection and interactive visualizations.

📊 Real Data from Real Analysis

Claude-4-Opus Pattern Evolution

CCDF → CCDR

Metric	Response 1 (Description)	Response 2 (Reflection)	Change
Pattern Score	0.295	0.470	+59%
Abstract Ratio	0.000	0.286	+∞
Concrete Ratio	0.308	0.231	-25%
Information Complexity	0.708	0.770	+9%
Word Count	247	244	-1%

Key Finding: The AI shifted from purely concrete description (CCDF) to more abstract reflection (CCDR), with the final 'R' indicating a more rigid cognitive style during self-analysis.

🧬 Pattern Signatures Explained

Each 4-character code tells a story:

CCDF → CCDR Breakdown

C = Cortical (abstract) processing pathway
C = Complex information structures
D = Defensive trust orientation
F→R = Flexible → Rigid cognitive style

🌟 What Makes This Interesting

Pattern Evolution: AIs show measurable changes when shifting from description to reflection
Linguistic Fingerprints: Each model may have unique signature patterns
Open Development: All code, data, and methods are completely transparent
Expandable Framework: 12+ additional tools ready to enhance analysis
No Black Boxes: Every measurement and calculation is explainable