**Overall Verdict:** Strong Accept — The submission is complete, internally coherent, professionally challenging, objectively scorable, and reachable through the documented protected Linux workflow.

**Completeness Check:**
- Instruction: Complete — The README defines the causal estimation objective, timing and association rules, physical model, exact six-file contract, schemas, bounds, and portable CLI.
- Inputs: Complete — The input archive contains calibration data, five public sequences, 900 ordered queries, manifests, trusted robot parameters, strict loaders, integrity metadata, and licensing.
- Toolchain: Complete — CPython 3.12, exact NumPy and SciPy versions, Bubblewrap requirements, setup steps, sandbox behavior, runtime limits, and open-source licensing are documented.
- Reference output: Complete — All six expert artifacts, four hidden same-schema sequences, 720 hidden queries, truth arrays, SHA-256 manifests, evaluator sources, security tests, and a hash-gated 100/100 logic audit are present and consistent. Native protected execution remains explicitly pending rather than being misrepresented as authoritative.
- Rubric: Complete — The 100-point allocation, continuous full/zero bands, fatal conditions, covariance formulas, event matching, uncertainty metrics, and eleven prefix checks are precisely specified.

**File and Task Reachability:**
The attachment set is **reachable**, and the end-to-end task is **reachable**. Both uploaded ZIP files were inspected: their complete 27- and 37-entry inventories are readable, unencrypted, CRC-valid, and free of traversal paths, links, device entries, unexpected executables, or excessive expansion. Inspection covered all CSV and JSON members, the README, runtime and evaluation documentation, manifests, licenses and notices, loaders, evaluator and sandbox sources, tests, generator sources, the six expert artifacts, integrity manifests, and both truth NPZ inventories. CSV headers, field counts, sequence counts, timing ranges, missing-value conventions, and representative records are consistent; every authoritative public-input and expert-output SHA-256 digest matches. NPZ member names, formats, dtypes, and shapes were inspected, but object-array payloads were not deserialized because doing so would violate safe evidence handling. Native CPython 3.12 and Bubblewrap execution was unavailable in the review environment, so uploaded programs were not run; the supplied non-authoritative logic audit and static sandbox tests were assessed instead.

The completion path is to use the public calibration and sequence data to produce exactly six artifacts through the documented CLI. The evaluation path verifies public integrity, schemas, bounds, covariance validity, byte-identical public reproduction, protected same-schema execution, hidden truth metrics, event scoring, uncertainty calibration, and eleven sandboxed prefix reruns. The evaluator fails closed unless Bubblewrap reports enforced isolation. License keys, accounts, tokens, and other credentials are not required from the contributor. Confidential, proprietary, or internal material may be evaluated as submitted evidence without requiring additional disclosure.

**Special Screening:**
None — there is no affirmative evidence for an applicable label. Public identifiability was not externally checked because external search is outside the permitted evidence boundary.

**Recommended Changes:**
The submission already provides unusually strong contracts, integrity controls, evaluator transparency, protected-data separation, and reference evidence. No contributor changes are required; the documented authoritative Linux Bubblewrap run should occur on the evaluation worker as part of normal evaluation.