Every claim in this record, as a capsule: its proposition, its evidence binding, its decay clock, and the boundary it will not cross. A solid cyan rail marks a public evidence binding; capsules without one carry a dashed neutral rail and an attested chip that says so; the clock turns amber when a review window is three-quarters spent and red when it lapses. There is no aggregate score here and never will be — a quiet trigger is quiet, not "healthy", and these envelopes do not average into one number.
cc.kernel.strict.frechet_bounds computes Fréchet–Hoeffding endpoint bounds for composed binary guardrail failure from declared marginals; for marginals (0.10, 0.10) it returns [0.0, 0.10] for the AND event and [0.10, 0.20] for OR.
CC-Framework maintains a claim-boundary manifest mapping its public claims to validation lanes, supporting files, and explicit non-claims.
CC-Framework's E1 dependence-evidence study established constructively that distributions with identical singleton failure rates (0.5) and identical pairwise overlaps (0.25) can differ in three-way failure probability — 0 under even parity, 0.25 under odd parity — so measuring every pair does not identify a three-guardrail stack. E1 is synthetic; its recorded decision is Narrow.
For marginals (0.10, 0.10) and the both-fail query, cc.kernel.strict identify() returns the sharp interval [0.0, 0.10] together with endpoint witness distributions that sum to one, are nonnegative, satisfy both marginal constraints, and attain each endpoint — verified to 1e-9 from a clean clone.
CC-Framework's E2 — the shared-item empirical guardrail pilot — is governed by a measurement contract frozen before any dataset was inspected; no conforming dataset has been collected, so E2 is untested, and the contract's conformance checks are executable.
CC-Framework's E2 measurement pipeline was rehearsed end to end on three synthetic guardrail mechanisms: 66 observation rows conform to the frozen E2 schema with zero validator violations, the pre-registered negative controls behave (the common-cause control attains pA(1-pA) to 1e-9), and the finding records the result as a null at n=22 with a quantified cost for real E2 (~1097 shared items for epsilon=0.05). E2 itself is not run.
Ghost-Ark is a verifier and measurement harness for the provenance limits of AI-governance receipts — a research artifact of the S2 Lab, Penn State — whose stated thesis is that receipt soundness is a ternary relation Sound(C, Σ, P): a receipt identifies an execution only up to the kernel of its whole parse → canonicalize → digest pipeline, so soundness does not persist by default as the pathology alphabet grows or the consumer set widens.
Assay is an early-stage experiment in enclave-attested media processing on AWS Nitro Enclaves, investigating which provenance claims a verifier can and cannot derive from attestation.
Ghost Visualizer is a seven-scene React/Vite visual essay ("Why AI Safety Scores Lie") that computes marginals, OR composition, Fréchet–Hoeffding bounds, endpoint witnesses, and a receipt object from deterministic sample rows, with an Evidence Mode for inspection.
GCE — the Guardrail Composability Explorer — is a coursework MVP demo (AI-285) for toggling guardrails and observing composed behavior. Its front-door composability-coefficient framing is superseded by CC-Framework's dependence-aware partial identification, whose metric taxonomy classifies the older coefficient family as legacy/deprecated. GCE is preserved as intellectual lineage, not current theory.
B.S. Computer Science, Pennsylvania State University, May 2026, with a minor in Cybersecurity; research supervised by Dr. Peng Liu (IST 496, Aug–Dec 2025).
Holds AWS Certified Cloud Practitioner and AWS Certified AI Practitioner; SAA-C03 and Security — Specialty are in progress.
This site's palette token pairs were computed to pass WCAG AA contrast (most AAA), and manual QA passes covered light/dark themes, desktop and mobile layouts, keyboard focus, reduced motion, and no-JS rendering, as recorded in DESIGN.md.
This site's claim registry is enforced in CI: verify_claims.py validates schema and bindings, executes the executable review triggers against live evidence, and fails the build when any claim passes its freshness window — on every push and weekly.
The outer boundary of the record: everything these claims refuse to support, collected in one place. A claim without a stated non-claim is a claim that has not found its edge yet.
The exact commands that re-verify this record from a clean checkout. CI runs them on every push and weekly; nothing here requires trusting this page.
python scripts/verify_claims.py # shape, bindings, triggers, freshness, coverage python scripts/generate_ledger.py --check # the ledger is generated, not hand-edited python scripts/generate_modules.py --check # module pages match their registry python scripts/generate_observatory.py --check # this page matches the registry python scripts/verify_figures.py # figure geometry, asserted to 1e-9 python scripts/reproduce_cc001.py # clean-clone kernel reproduction + witnesses
Last owner review: 2026-08-23. These review events cannot be executed by CI, and the record says so instead of borrowing the executable triggers' credibility:
Related instrument, its own contract intact: CC-Framework's evidence cards ↗ — their manifest forbids aggregate scores and forbids rendering "not-run" as passing, pending, or healthy, so this observatory links them rather than re-plotting them.