Studying structural reliability and confidence behavior in deployed AI systems.
Internal research instruments. Not consumer tools.
A focused research domain examining detection reliability and confidence behavior across modalities. The objective is not classification performance alone, but understanding where detection systems appear reliable — and where they fail under operational conditions.
A research instrument evaluating confidence behavior in large language model detection.
Used internally to analyze structural reliability in AI-generated text classification.
A research system analyzing artifact reliance and cross-generator variance in synthetic image detection.
This work examines how detection stability changes across compression, model evolution, and adversarial modification.
A research instrument examining temporal consistency and detection breakdown in synthetic or manipulated video.
This research focuses on confidence behavior across frames, edits, and generative manipulation techniques.
