Research feedback requested: Epistemic Shield — adversarial epistemic calibration for LLM outputs

I built an experimental framework that treats an LLM’s first answer as a provisional hypothesis rather than as publishable output.

The pipeline:

The conceptual motivation is what I call an “impostor-like epistemic mechanism”: deliberately introducing structured skepticism when the cost of unsupported assertions is high.

I am looking for technical criticism, suggestions for benchmarks, and collaborators interested in testing whether this architecture actually improves calibration or hallucination resistance.

Code and documentation: sam-siram/epistemic-shield: Framework de Calibración Epistémica, Autocrítica Adversarial y Penalización Asimétrica para LLMs.