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Releases: Sulkysubject37/resED

v1.3.0-tnnls-submission

09 Feb 10:02

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Release Notes - v1.3.0-tnnls-submission

Overview

This release marks the formal submission of the manuscript "Reliability is a System Property" to the IEEE Transactions on Neural Networks and Learning Systems (TNNLS). The repository has been refined to meet archival standards, with an emphasis on transparency, reproducibility, and professional hygiene.

Key Changes

1. Manuscript Submission

  • Submission Target: IEEE TNNLS Regular Paper.
  • Anonymization: The main manuscript has been anonymized for double-blind review.
  • Supporting Documents: Generated official Title Page (DOCX), Conflict of Interest Statement (PDF), and Cover Letter (PDF).
  • Packaging: Created main_manuscript.zip and supplementary_material.zip following IEEE guidelines.

2. Codebase Professionalization

  • Editorial Cleanup: Removed AI-generated narrative slop and redundant internal development markers (Phases 0-12) from all Python source files.
  • Comment Pruning: Editorial refinement of inline comments to focus on mathematical invariants and safety contracts.
  • Consistency: Standardized naming conventions across resed/, experiments/, and tests/.

3. Documentation & Transparency

  • Documentation Overhaul: Renamed and restructured all technical reports in docs/ to follow an academic, descriptive format (e.g., universality_validation.md, biological_evaluation.md).
  • Supplementary Index: Added a comprehensive SUPPLEMENTARY_README.md to guide reviewers through the experimental and validation suite.
  • Reference Implementation: Linked to the resLIK R package on CRAN as the formal reference for RLCS logic.

4. Technical Refinements

  • Limitation Framing: Explicitly documented "Normalization Blindness" in LayerNorm-based architectures.
  • Numerical Integrity: Verified that all core experimental results (AUROC scores) remain bit-exact matches to the reported figures in the manuscript.

Repository Status

  • Branch: main
  • Tag: v1.3.0-tnnls-submission
  • License: MIT License
  • Copyright: (c) 2026 MD. Arshad

The resED repository is provided for transparency and reproducibility; it is not required to reproduce the claims of the paper.