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AI governance essays, reasoning systems notes, experiment logs, and technical writing across BioAI and engineering practice.

Current ViewScientific & BioAI InfrastructureSearch: AI Hallucination
How Do You Trust the AI Auditor? STEM-AI v1.1.2 and Memory-Contracted Bio-AI Audits
Scientific & BioAI Infrastructure
STEM-AI:Soverign Trust Evaluator for Medical AI Artifacts

How Do You Trust the AI Auditor? STEM-AI v1.1.2 and Memory-Contracted Bio-AI Audits

STEM-AI v1.1.2 binds a bio/medical AI repository audit to a machine-checkable memory contract, then demonstrates it on a real open-source bioinformatics repository.

Evidence-aware scientific systems#AI#AGI#AI Ethics#AI Alignment#AI Governance#AI Hallucination#Biomedical#Bioinformatics#Mlops#Deep Learning#Machine Learning#Cognitive Science#Developer Tools#DevOps#AI Research#Scientific Integrity#Business Strategy#AI Code#Contextengineering#Architecture#Data Orchestration#Code Review
When an AI Pipeline Passes — But One Path Still Must Be Held: EXP-034
Scientific & BioAI Infrastructure
RExSyn Nexus-Bio

When an AI Pipeline Passes — But One Path Still Must Be Held: EXP-034

EXP-034 tested whether a method-locked Bio-AI governance pipeline could survive modal expansion, AlphaFold EBI observer wiring, and AG-live measurement without breaking its PASS/BLOCK judgment baseline.

Evidence-aware scientific systems#AI#AGI#AI Ethics#AI Governance#AI Alignment#AI Hallucination#Biomedical#Bioinformatics#SR9/DI2#Machine Learning#Deep Learning#Cognitive Science#Data Orchestration#Code Review
When AI Models Fight, Truth Wins: The “Eureka” Moment for Tired Researchers
Scientific & BioAI Infrastructure

When AI Models Fight, Truth Wins: The “Eureka” Moment for Tired Researchers

To the grad student staring at a pLDDT of 90 and wondering why the ligand won’t bind.

Evidence-aware scientific systems#AI#AGI#AI Ethics#AI Governance#AI Hallucination#Biomedical#SR9/DI2#Mlops#AI Research#Scientific Integrity#Software Development
Orchestrating AlphaFold 3 & 2 with Python: Handling AI Hallucinations using Adapter Patter (Trinity Protocol Part 1)
Scientific & BioAI Infrastructure
RExSyn Nexus-Bio

Orchestrating AlphaFold 3 & 2 with Python: Handling AI Hallucinations using Adapter Patter (Trinity Protocol Part 1)

Learn how to orchestrate AlphaFold 3 and AlphaFold 2 with Python using the Adapter Pattern to detect AI hallucinations, measure structural drift, and improve protein prediction reliability.

Evidence-aware scientific systems#AI#Mlops#Bioinformatics#Architecture#Scientific Integrity#Biomedical#AI Alignment#AI Governance