Chris Nennemann
be9cf9c5d9
New features: - 12 interactive visualizations (ietf viz): t-SNE landscape, similarity heatmap, score distributions, timeline, bubble explorer, radar charts, author network graph, category treemap, quality vs overlap, org bar chart, ideas chart, and interactive draft browser - Interactive draft browser (browser.html): filterable by category, keyword, score sliders with sortable table and expandable detail rows - arXiv paper (paper/main.tex): 13-page manuscript with all findings - Gap analysis: 12 identified under-addressed areas - Author network: collaboration graph, org contributions, cross-org analysis - Draft generation from gaps (ietf draft-gen) - Auto-load .env for API keys (python-dotenv) New modules: visualize.py, authors.py, draftgen.py New reports: timeline, overlap-matrix, authors, gaps New deps: plotly, matplotlib, seaborn, scipy, scikit-learn, networkx, python-dotenv Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
16 KiB
16 KiB
Overlap Matrix Report
Generated 2026-02-28 10:28 UTC — 260x260 pairwise similarities
Top 50 Most Similar Pairs
Per-Category Internal Overlap
| Category | Drafts | Avg Pairwise Sim | Most Similar Pair |
|---|---|---|---|
| A2A protocols | 92 | 0.758 | rosenberg-aiproto / rosenberg-aiproto-nact (0.999) |
| AI safety / guardrails / alignment | 1 | — | — |
| AI safety/alignment | 36 | 0.765 | rosenberg-aiproto-cheq / rosenberg-cheq (0.994) |
| Agent discovery / registration | 14 | 0.779 | campbell-agentic-http / narvaneni-agent-uri (0.863) |
| Agent discovery/reg | 57 | 0.759 | rosenberg-aiproto / rosenberg-aiproto-nact (0.999) |
| Agent identity/auth | 98 | 0.740 | lake-pocero-authkem-ikr-e / pocero-authkem-ikr-edhoc (0.999) |
| Agent-to-agent communication protocols | 16 | 0.785 | campbell-agentic-http / narvaneni-agent-uri (0.863) |
| Autonomous netops | 60 | 0.745 | ahn-nmrg-5g-security-i2ns / ahn-opsawg-5g-security-i2 (0.997) |
| Autonomous network operations | 5 | 0.785 | zhang-agent-gap-network / zhang-rtgwg-ai-agents-tro (0.826) |
| Data formats / semantics for AI interop | 3 | 0.801 | liu-agent-context-protoco / narvaneni-agent-uri (0.814) |
| Data formats/interop | 102 | 0.715 | rosenberg-aiproto / rosenberg-aiproto-nact (0.999) |
| Human-agent interaction | 22 | 0.739 | rosenberg-aiproto-cheq / rosenberg-cheq (0.994) |
| Identity / authentication for AI agents | 13 | 0.784 | chen-agent-decoupled-auth / song-oauth-ai-agent-autho (0.882) |
| ML traffic mgmt | 23 | 0.739 | tong-network-agent-use-ca / yu-dmsc-ai-agent-use-case (0.892) |
| ML-based traffic management / optimization | 1 | — | — |
| Model serving/inference | 13 | 0.733 | gaikwad-llm-benchmarking- / gaikwad-llm-benchmarking- (0.959) |
| Other AI/agent | 21 | 0.709 | ietf-httpbis-layered-cook / ietf-httpbis-rfc6265bis (0.988) |
| Policy / governance / ethical frameworks | 2 | 0.882 | chen-agent-decoupled-auth / song-oauth-ai-agent-autho (0.882) |
| Policy/governance | 60 | 0.737 | ahn-nmrg-5g-security-i2ns / ahn-opsawg-5g-security-i2 (0.997) |
Category Cross-Overlap
Average similarity between drafts in different categories.
| A2A protoc | AI safety | AI safety/ | Agent disc | Agent disc | Agent iden | Agent-to-a | Autonomous | Autonomous | Data forma | Data forma | Human-agen | Identity / | ML traffic | ML-based t | Model serv | Other AI/a | Policy / g | Policy/gov | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| A2A protocol | 0.76 | 0.75 | 0.74 | 0.77 | 0.76 | 0.73 | 0.77 | 0.74 | 0.76 | 0.77 | 0.73 | 0.74 | 0.76 | 0.73 | 0.74 | 0.71 | 0.72 | 0.75 | 0.74 |
| **AI safety / ** | 0.00 | 0.78 | 0.77 | 0.75 | 0.76 | 0.76 | 0.71 | 0.73 | 0.75 | 0.72 | 0.75 | 0.78 | 0.70 | 0.72 | 0.69 | 0.71 | 0.88 | 0.76 | |
| AI safety/al | 0.76 | 0.76 | 0.74 | 0.75 | 0.75 | 0.71 | 0.73 | 0.75 | 0.73 | 0.74 | 0.77 | 0.71 | 0.72 | 0.70 | 0.71 | 0.78 | 0.75 | ||
| Agent discov | 0.78 | 0.77 | 0.74 | 0.78 | 0.74 | 0.77 | 0.78 | 0.74 | 0.75 | 0.78 | 0.74 | 0.76 | 0.71 | 0.73 | 0.76 | 0.75 | |||
| Agent discov | 0.76 | 0.73 | 0.77 | 0.74 | 0.76 | 0.77 | 0.73 | 0.74 | 0.76 | 0.73 | 0.75 | 0.71 | 0.72 | 0.75 | 0.74 | ||||
| Agent identi | 0.74 | 0.74 | 0.71 | 0.72 | 0.73 | 0.72 | 0.73 | 0.75 | 0.70 | 0.71 | 0.69 | 0.71 | 0.76 | 0.73 | |||||
| Agent-to-age | 0.79 | 0.75 | 0.78 | 0.79 | 0.74 | 0.75 | 0.78 | 0.75 | 0.77 | 0.72 | 0.73 | 0.76 | 0.75 | ||||||
| Autonomous n | 0.74 | 0.76 | 0.73 | 0.71 | 0.72 | 0.73 | 0.74 | 0.76 | 0.71 | 0.72 | 0.71 | 0.72 | |||||||
| Autonomous n | 0.79 | 0.78 | 0.73 | 0.74 | 0.76 | 0.75 | 0.79 | 0.72 | 0.73 | 0.73 | 0.73 | ||||||||
| Data formats | 0.80 | 0.74 | 0.75 | 0.77 | 0.74 | 0.76 | 0.71 | 0.73 | 0.76 | 0.74 | |||||||||
| Data formats | 0.72 | 0.72 | 0.74 | 0.71 | 0.72 | 0.70 | 0.71 | 0.73 | 0.72 | ||||||||||
| **Human-agent ** | 0.74 | 0.75 | 0.72 | 0.73 | 0.71 | 0.72 | 0.76 | 0.74 | |||||||||||
| Identity / a | 0.78 | 0.73 | 0.75 | 0.71 | 0.73 | 0.79 | 0.76 | ||||||||||||
| ML traffic m | 0.74 | 0.75 | 0.73 | 0.71 | 0.71 | 0.71 | |||||||||||||
| ML-based tra | 0.00 | 0.73 | 0.73 | 0.72 | 0.72 | ||||||||||||||
| Model servin | 0.73 | 0.70 | 0.69 | 0.70 | |||||||||||||||
| Other AI/age | 0.71 | 0.71 | 0.71 | ||||||||||||||||
| Policy / gov | 0.88 | 0.77 | |||||||||||||||||
| Policy/gover | 0.74 |
Most Unique Drafts (max similarity < 0.70)
No drafts with max similarity below 0.70.