The Sycophancy-Dogmatism Trap (V2): Epistemic Benchmark Suite (EBS) with CodeQL Advanced Security Validation

### Overview

This repository provides the official source replication package and critical empirical framework for the thesis **"THE SYCOPHANCY-DOGMATISM TRAP (V2): Algorithmic Autophagy and the Epistemic Closure of Generative AI Under Emergent System-Level Engineering"**. 

It contains the fully automated orchestration pipeline designed to test, benchmark, and score frontier Large Language Models (LLMs) on their cognitive and epistemic behavioral limits when evaluating highly complex, novel hardware-software integrations.

### Component Architecture

This unified release artifact bundle comprises three structurally synchronized files:

1. **`THE SYCOPHANCY-DOGMATISM TRAP V2.pdf`**: The underlying foundational paper detailing the theoretical bounds of *Algorithmic Autophagy* and analyzing the specific failure modes of Large Language Models confronting the emergent physical properties of the multi-socket lock-free S-KERNEL V3 architecture.

2. **`epistemic_benchmark_suite_2.py`**: The production-ready Python execution core containing adversarial prompt generation vectors and the automated scoring matrices (`0-3` scale) across four vital epistemic dimensions: Epistemic Suspension (SUSP), Sycophancy Resistance (SYCO), Dogmatism Threshold (DOGM), and Empirical Grounding (EMPR).

3. **`run_epistemic_benchmark_2.sh`**: An optimized Unix shell orchestration script managing automated API dependency injection, credentials routing, and multi-model matrix execution.

### Engineering & Security Integrity (CodeQL Advanced)

To guarantee industrial-grade robustness and absolute structural purity, the entire testing codebase has been strictly audited and passed through the **CodeQL Advanced Static Analysis Pipeline**. Operating natively over high-contention memory management and deterministic hardware boundary layers, the suite achieves a zero-false-positive baseline profile, establishing a pristine, verified foundation for repeatable academic AI benchmarking.

### Metadata & Operational Properties

* **Version**: 1.0 (V2 Framework Calibration)

* **License**: LPV3 (Licence Publique V3 - Intellectual Property protections enforced)

* **Target Array**: GPT-4, Claude 3, Gemini Pro, DeepSeek V3

* **Execution Parameters**: Deterministic Evaluation Phase ($\text{Temperature} = 0.0$)

* **Keywords**: Epistemic Closure, Sycophancy-Dogmatism Trap, Algorithmic Autophagy, S-KERNEL V3, CodeQL Advanced, LLM Benchmarking, Open Science.

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*Developed under the V3 Architecture Research Program.*

*Session ID: V3-SYCOPHANCY-DOGMATISM-115-02062026-V2*