[Re] Network Deconvolution

Which comparison in the article can be tested using a rights-cleared small image dataset while retaining a clearly stated scope limit?

Use identical evaluator-owned splits and training budgets, independently rescore predictions, and avoid generalizing a small-data result to ImageNet.

What you could produce

• Versioned protocol, input and environment manifest, and independent per-case comparison table including uncertainty and incomplete cases.

Before you use it

• Exact article-specific dependencies, data and build requirements remain uninspected.

Limits to keep in view

• No research code was executed; no independent scientific verification has been performed.
• The current qualified pilot is self-contained Python 3.13 with a 90-second author deadline. This article's environment has not been qualified for that path.
• Published source metadata and a historical review do not establish compatibility, successful reproduction, operator independence or current scientific correctness.

Source and permission context

Obadage, Rochana R.; Thennakoon, Kumushini; Rajtmajer, Sarah M.; Wu, Jian. [Re] Network Deconvolution. ReScience C 10(1), #4; 10.5281/zenodo.15321683.

Catalog listing reviewed. This review covers the description and source links displayed here.

ReScience/Zenodo metadata reviewed; exact CC-BY-4.0 evidence is manuscript-scoped.

Reviewed 2026-09-14. Copying or adapting source files remains subject to their own terms.

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