# Verified Database Counts

**Source**: `data/drafts.db` -- queried 2026-03-08
**Purpose**: Single source of truth for all counts, replacing inconsistent numbers across blog posts and reports.

---

## Core Tables

| Table | Count | Notes |
|-------|-------|-------|
| drafts | 434 | Up from 361 after 2026-03-07 fetch |
| ratings | 434 | 1:1 with drafts |
| authors | 557 | Unique persons from Datatracker |
| ideas | 462 | Re-extracted 2026-03-08, see "Ideas Count History" below |
| gaps | 11 | Not 12 -- see gap list below |
| embeddings | 434 | 1:1 with drafts |
| draft_authors | 1,057 | Draft-author links |
| llm_cache | 1,397 | Cached API calls |

## False Positive Analysis

73 drafts flagged as `false_positive = 1` in ratings table (new column added 2026-03-08).

| Criteria | Count |
|----------|-------|
| Relevance <= 2 (auto-flagged) | 38 |
| Relevance 3+ but clearly not AI-agent (manually reviewed) | 35 |
| **Total false positives** | **73** |
| **Drafts excluding false positives** | **361** |

### Relevance Score Distribution (all 434 drafts)

| Relevance | Count |
|-----------|-------|
| 1 | 2 |
| 2 | 36 |
| 3 | 102 |
| 4 | 196 |
| 5 | 98 |

## Category Counts (excluding false positives)

All categories normalized to short-form names (21 legacy long-form entries migrated 2026-03-08).

| Category | Count |
|----------|-------|
| Data formats/interop | 146 |
| A2A protocols | 146 |
| Agent identity/auth | 127 |
| Autonomous netops | 103 |
| Policy/governance | 97 |
| Agent discovery/reg | 82 |
| ML traffic mgmt | 77 |
| AI safety/alignment | 44 |
| Model serving/inference | 42 |
| Human-agent interaction | 33 |
| Other AI/agent | 18 |

Note: Drafts average ~2.4 categories each, so these sum to more than 361.

## Gap List (11 gaps, not 12)

| ID | Topic | Severity | Category |
|----|-------|----------|----------|
| 37 | Multi-Agent Consensus Protocols | high | A2A protocols |
| 38 | Agent Behavioral Verification | critical | AI safety/alignment |
| 39 | Cross-Protocol Agent Migration | medium | Agent discovery/reg |
| 40 | Real-Time Agent Rollback Mechanisms | high | Autonomous netops |
| 41 | Agent Resource Accounting and Billing | medium | new |
| 42 | Federated Agent Learning Privacy | high | Policy/governance |
| 43 | Agent Capability Negotiation | medium | A2A protocols |
| 44 | Cross-Domain Agent Audit Trails | high | Agent identity/auth |
| 45 | Agent Failure Cascade Prevention | critical | AI safety/alignment |
| 46 | Human Override Standardization | high | Human-agent interaction |
| 47 | Agent Performance Benchmarking | medium | new |

Blog posts reference 12 gaps with different names (e.g., "Agent Resource Exhaustion Protection" vs DB's "Agent Resource Accounting and Billing"). The blog list appears to be an editorial rewrite, not raw pipeline output. The missing 12th gap may be "Cross-Protocol Translation" or "Agent Data Provenance" which appear in blog posts but not in the database.

## Ideas Count History

The database currently contains **462 ideas** across **415 drafts**. This is the fourth count encountered:

| Source | Count | Date | Likely Explanation |
|--------|-------|------|-------------------|
| Blog post 5 filename | 1,262 | ~2026-03-03 | Pre-expansion dataset (260 drafts), before dedup |
| Blog post 5 text / master stats | 1,780 | ~2026-03-05 | Post-expansion (361 drafts), before dedup |
| Previous database | 419 | 2026-03-08 | After `dedup_ideas` run (0.85 threshold) or re-extraction with different params |
| Current database | 462 | 2026-03-08 | After re-extraction for 38 drafts missing ideas (474 total drafts, 59 still without ideas) |

### Ideas by Type (current DB)

| Type | Count |
|------|-------|
| architecture | 107 |
| protocol | 106 |
| extension | 84 |
| mechanism | 74 |
| requirement | 47 |
| pattern | 40 |
| framework | 3 |
| format | 1 |

### Ideas per Draft Distribution

| Ideas/Draft | Drafts |
|-------------|--------|
| 1 | 370 |
| 2 | 43 |
| 3 | 2 |
| 0 (no ideas) | 59 |

The near-uniform 1-idea-per-draft (89% of drafts with ideas) suggests either aggressive dedup or a re-extraction with constrained output. The original pipeline extracted 1-4 ideas per draft, so the 1,780 figure likely reflects pre-dedup counts.

### Convergence Analysis (2026-03-08)

Cross-organization idea convergence analysis (threshold: 0.75 SequenceMatcher similarity):

| Metric | Value |
|--------|-------|
| Total ideas | 462 |
| Unique clusters | 398 |
| Cross-org convergent ideas | 132 |
| Convergence rate | 33% |

Top convergent ideas by organization count:
- **Fully Adaptive Routing Ethernet for AI** — 14 orgs (Baidu, Broadcom, China Mobile, etc.)
- **AI Agent Protocol Framework** — 7 orgs, 3 drafts
- **Natural Language Protocol for Agent Comm** — 7 orgs
- **LISP-based geospatial intelligence network** — 6 orgs
- **MCP-Based Network Management Plane** — 4 orgs (Deutsche Telekom, Huawei, Orange, Telefonica)

## Actions Taken (2026-03-08)

1. **Category normalization**: Updated 21 ratings rows from legacy long-form category names to canonical short forms. All 11 categories now consistent.
2. **False positive flagging**: Added `false_positive` column to ratings table. Flagged 73 drafts (38 with relevance <= 2, 35 manually reviewed at relevance 3+).
3. **Schema migration**: Updated `db.py` schema and migration code to include `false_positive` column.
4. **This document**: Created as single source of truth for counts.
