Evidence row 1262399

What was observed

{
  "endpoints": [
    [
      "x402",
      "https://intel.degenscan.io/v1/ai/research"
    ]
  ],
  "name": "Degenscan Intel",
  "owner_address": "0x21f4a2da07bcce60878cab223358d11ad8f11a94",
  "raw": {
    "accepts": [
      {
        "amount": "2000",
        "asset": "0x833589fCD6eDb6E08f4c7C32D4f71b54bdA02913",
        "extra": {
          "name": "USD Coin",
          "version": "2"
        },
        "maxTimeoutSeconds": 60,
        "network": "eip155:8453",
        "payTo": "0x21f4A2DA07bccE60878cAb223358D11aD8F11a94",
        "scheme": "exact"
      },
      {
        "amount": "2000",
        "asset": "EPjFWdd5AufqSSqeM2qN1xzybapC8G4wEGGkZwyTDt1v",
        "extra": {
          "feePayer": "GVJJ7rdGiXr5xaYbRwRbjfaJL7fmwRygFi1H6aGqDveb"
        },
        "maxTimeoutSeconds": 60,
        "network": "solana:5eykt4UsFv8P8NJdTREpY1vzqKqZKvdp",
        "payTo": "GptpyPWpqUJHXs7G1Xp7zMs1MXidunsWDW4APKArRhez",
        "scheme": "exact"
      }
    ],
    "description": "AI research momentum: number of new arXiv papers in the last 7 and 30 days per topic (RAG, agents, fine-tuning, MCP, evaluation, quantization, multimodal, reasoning, safety, inference). Market data only — not investment advice.",
    "extensions": {
      "bazaar": {
        "info": {
          "input": {
            "method": "GET",
            "queryParams": {
              "topic": "rag"
            },
            "type": "http"
          },
          "output": {
            "example": {
              "items": [
                {
                  "papers_30d": 1650,
                  "papers_7d": 420,
                  "topic": "agents",
                  "weekly_pace_vs_30d": 1.09
                }
              ]
            },
            "type": "json"
          }
        },
        "schema": {
          "$schema": "https://json-schema.org/draft/2020-12/schema",
          "properties": {
            "input": {
              "additionalProperties": false,
              "properties": {
                "method": {
                  "enum": [
                    "GET"
                  ],
                  "type": "string"
                },
                "queryParams": {
                  "properties": {},
                  "type": "object"
                },
                "type": {
                  "const": "http",
                  "type": "string"
                }
              },
              "required": [
                "type",
                "method"
              ],
              "type": "object"
            },
            "output": {
              "properties": {
                "example": {
                  "type": "object"
                },
                "type": {
                  "type": "string"
                }
              },
              "required": [
                "type"
              ],
              "type": "object"
            }
          },
          "required": [
            "input"
          ],
          "type": "object"
        }
      }
    },
    "lastUpdated": "2026-10-29T21:14:39.896Z",
    "quality": {
      "l30DaysTotalCalls": 1,
      "l30DaysUniquePayers": 1,
      "lastCalledAt": "2026-10-29T21:14:39.74Z"
    },
    "resource": "https://intel.degenscan.io/v1/ai/research",
    "serviceName": "Degenscan Intel",
    "tags": [
      "finance",
      "markets",
      "events",
      "crypto",
      "stocks"
    ],
    "type": "http",
    "x402Version": 2
  },
  "source": "x402_bazaar",
  "summary": "AI research momentum: number of new arXiv papers in the last 7 and 30 days per topic (RAG, agents, fine-tuning, MCP, evaluation, quantization, multimodal, reasoning, safety, inference). Market data only — not investment advice."
}

What the leaf hashes

{"body":"cc8496278a5c14ff8f5a123c7811fdd98a33c1bdcb4a8ad784403ec5ee65db48","id":1262399,"kind":"listing","method":"sync.x402_bazaar/1","observed_us":1793385558869357,"prev":null,"subject":"x402_bazaar:https://intel.degenscan.io/v1/ai/research","subject_kind":"source_record"}

Proof

Fold these into the leaf in order, hashing each sorted pair with keccak256, to reach the root of 2026-10-30 (243099 rows).

1. 0x311b7ae14271a621f83fb11c50121734c69f7496a80becd8dc00549b7563682a
2. 0xd3c32e922901e273a835b54aa6e471712d9d687d8d7b7637f671ada0cce96e44
3. 0x030c55c3c4722afcecde523a1b51e084da307782d14a3225f674b8e74b395354
4. 0x5f0effe82d3705ce1f9e4dfb7348a651406f26b43061e24d42c4c0419d738033
5. 0xedca25b40d78d32bdcd430c88a68f17a17a0968533d9510af202f001bf7ea9b4
6. 0x643001f6128999bf196f493eb8f5e65ae5a6ff8ef85b5e58509ea488cf5cda35
7. 0xa323f950dc4e7d4edd24d283a5929f07600685c0644f66b6caa588ec9f062009
8. 0x8fd9455d558438afc930de6331d32c4fdd5419d33896d6eb00d0beea3c7b0d3b
9. 0x3f504db84d3833fc76e9aeecd9620e15acab626d60f5f7f7979525d4aa45fdf8
10. 0x123784351954f98382aaa715043b93a272c6334042ecc52092bad04e73d24ad1
11. 0x3bc6ecf4111f73368ed3c51d1f42e543899e649d8d5e8cda11844ee6a7400a08
12. 0xd658f5ebf53f5f4d9e144502aadc553401a7b6fa9aa8d2999117181fae286e99
13. 0xa731ea0a53ef052371d2f4f5c1c8f41649e1bf40a860f84529dbcb9601498e0d
14. 0xc1162ffd606c8e0e72ce94a16332c19bf77c27df8032f71c95d5690246968bbe
15. 0x6222037db785cc797fc8809e52e551d945c928d389b7ac947c037fb9af818562
16. 0x50ca74d7c8f26a46e9c3b8fb5e7f9ebcdfdcc1b7c863db3b6d2b7c12e24ca66f
17. 0xb0c9ef42e725578748f3119c9dbebf2fc437266bda013df29f98ed3ebe621403
18. 0x30a81d8fcef4e8f9e2877c62796cfc5612fc1b251127d531dee28f8dbd5c5147

Day root

0x0826c7ad6039e06a2360ca0a4a3a4fe7f2626c6dc19f71a37599386f78b39875

Chained

0x36b4c8a1063758f0b8765fa1bdf75fa92fb543cc183add3e261880ee2bd1f822

Published

On Arc Testnet, block 69923247: 0x8704744146c6967c8abc9e9a99de4db7283b29e840922ea83a69b6fe776e6861