Analytical benchmark
Deterministic scenarios cover metadata inflation from 1× through 16×. They are explicitly not production measurements.
AQPO studies predictive caching, verified segment materialization, and compact metadata views for open table layouts under post-quantum overhead.
Research checks and Pages deployment passing
AQPO sits between compute engines and authoritative catalogs. Optimization never replaces the source of truth.
Deterministic scenarios cover metadata inflation from 1× through 16×. They are explicitly not production measurements.
Automated checks validate latency ordering, metadata-read ordering, bounded ratios, and artifact labeling.
Manuscripts, raw scans, local paths, private email, and unauthorized attribution fail publication.
Illustrative model output. Production validation remains future work.
Detector outputs are probabilistic indicators, not proof of authorship or misconduct. Raw reports remain private because they contain manuscript-derived text.
The public repository contains sanitized analytical inputs, validation code, and a deny-by-default privacy check. It does not contain the manuscript or raw scan reports.
git clone https://github.com/darisisuresh/QuantaLake-AQPO.git
cd QuantaLake-AQPO
python3 -m unittest discover -s tests -v
python3 scripts/validate_evidence.py
python3 scripts/privacy_check.py