**Overall Verdict:** Accept — The submission is complete, coherent, objectively gradable, and operationally reachable, with only a reviewer-environment limitation preventing independent decoding of numerical HDF5 payloads.

**Completeness Check:**
- Instruction: Complete — The objective, event and flow conventions, temporal support, restrictions, deterministic runtime interface, deliverables, and exact output schema are consistently specified.
- Inputs: Complete — The input package contains the event stream, 45-row timestamp CSV, calibration, schema, documentation, pinned dependencies, license, and a schema validator; provenance hashes for the core inputs agree across packages.
- Toolchain: Complete — The CPU-only Python toolchain and solver dependencies are pinned, legally obtainable, and appropriate for the modest data scale; evaluator dependencies are separately pinned.
- Reference output: Complete — The protected package contains reference flow and validity data, a gold-format candidate, provenance, diagnostics, and an offline evaluator. Its recorded gold self-test passes all nine grouped mandatory gates.
- Rubric: Complete — The evaluator implements the documented schema, storage, range, EPE, angular, per-timestamp, high-motion, border-exclusion, and two-run determinism requirements. The zero-flow diagnostic fails four accuracy gates, demonstrating meaningful discrimination.

**File and Task Reachability:**
The attachment set is `partially_reachable` solely because the review environment lacked an HDF5 numerical decoder and video decoder. Both `event_flow_input_v1.zip` and `event_flow_reference_v1.zip` were inspected at their manifest byte counts; they are valid, unencrypted ZIP archives with safe paths, no duplicate entries or special filesystem objects, modest expansion, and successful internal integrity checks. Text, CSV, JSON, YAML, licenses, evaluator source/tests, generator provenance, archive inventories, HDF5 signatures and embedded dataset names, and the MP4 container structure were inspected. Numerical HDF5 arrays and diagnostic video frames were not independently decoded; consistent generator source, cross-package hashes, evaluator diagnostics, and embedded schema names mitigate this reviewer-tooling uncertainty.

The task is `reachable`: a solver can load the supplied asynchronous events, generate two deterministic `event_flow.h5` outputs using the declared CPU-only toolchain, and be evaluated offline against the separately packaged hidden reference and validity mask. Storage and memory requirements are modest, reference material is separated from solver-visible inputs, and no external service or hardware dependency is present. 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 — provenance affirmatively describes deterministic procedural generation without pretrained models or external assets. No evidence supports AI-generated core evidence, a public benchmark, or a synthetic defect fixture; public identifiability was not independently searched under the offline evidence boundary.

**Recommended Changes:**
The submission provides unusually strong documentation, provenance, integrity manifests, negative and positive diagnostics, and evaluator tests. No contributor changes are required. An admin-side execution of the supplied evaluator tests and diagnostics in the declared Python/HDF5 environment would close the remaining reviewer-tooling uncertainty.