Evidence row 67966

What was observed

{
  "endpoints": [
    [
      "x402",
      "https://api.particle.pro/v1/podcasts"
    ]
  ],
  "name": "Particle Pro",
  "owner_address": "0x59f3a6dcb6f482c53872dd8f8f9e1f9161a1c5f7",
  "raw": {
    "accepts": [
      {
        "amount": "10000",
        "asset": "0x833589fCD6eDb6E08f4c7C32D4f71b54bdA02913",
        "extra": {
          "name": "USD Coin",
          "version": "2"
        },
        "maxTimeoutSeconds": 300,
        "network": "eip155:8453",
        "payTo": "0x59f3a6dcb6f482c53872dd8f8f9e1f9161a1c5f7",
        "scheme": "exact"
      }
    ],
    "description": "List and search podcasts. Returns a paginated list of podcasts, with filters for topic, language, suitability tier, popularity, and format.",
    "extensions": {
      "bazaar": {
        "info": {
          "input": {
            "method": "GET",
            "queryParams": {
              "format_signal": [
                "interview"
              ],
              "guest_frequency": [
                "regular",
                "always"
              ],
              "language": "fr"
            },
            "type": "http"
          }
        },
        "schema": {
          "$schema": "https://json-schema.org/draft/2020-12/schema",
          "properties": {
            "input": {
              "additionalProperties": false,
              "properties": {
                "method": {
                  "enum": [
                    "GET"
                  ],
                  "type": "string"
                },
                "queryParams": {
                  "properties": {
                    "cursor": {
                      "description": "Opaque pagination cursor from previous response",
                      "type": "string"
                    },
                    "format_signal": {
                      "description": "Filter by detected production format. Pass a comma-separated list to match any of several formats — e.g. panel,call_in. Values mirror the format.signals field on podcast responses; a show can carry several signals.",
                      "items": {
                        "type": "string"
                      },
                      "type": "array"
                    },
                    "guest_frequency": {
                      "description": "Filter by how often episodes feature a guest. Pass a comma-separated list to match any of several buckets — e.g. regular,always for interview-driven shows, or never for shows that don't host guests. Only matches podcasts with enough analyzed episodes to judge; values mirror the format.guest_frequency field on podcast responses.",
                      "items": {
                        "type": "string"
                      },
                      "type": "array"
                    },
                    "has_ads": {
                      "description": "Filter by advertiser presence. Pass false to find ad-free shows — an assertion that requires the show to have enough analyzed episodes, so sparsely-analyzed podcasts are excluded rather than presumed ad-free.",
                      "enum": [
                        "true",
                        "false"
                      ],
                      "type": "string"
                    },
                    "has_video": {
                      "description": "Filter by whether episodes have discovered video versions (e.g. YouTube releases).",
                      "enum": [
                        "true",
                        "false"
                      ],
                      "type": "string"
                    },
                    "language": {
                      "description": "Filter by the podcast's language (ISO 639-1 code, e.g. 'en', 'fr'). Matches the primary language subtag, so 'fr' covers 'fr-FR'.",
                      "type": "string"
                    },
                    "limit": {
                      "description": "Results per page",
                      "format": "int64",
                      "type": "integer"
                    },
                    "max_avg_episode_minutes": {
                      "description": "Only podcasts whose average episode runs at most this many minutes.",
                      "format": "int64",
                      "type": "integer"
                    },
                    "max_episodes_per_week": {
                      "description": "Only podcasts publishing at most this many episodes per week on average (e.g. 0.5 for fortnightly-or-slower shows).",
                      "format": "double",
                      "type": "number"
                    },
                    "min_avg_episode_minutes": {
                      "description": "Only podcasts whose average episode runs at least this many minutes. Combine with max_avg_episode_minutes to target a length band (e.g. 20–40 minute commute shows).",
                      "format": "int64",
                      "type": "integer"
                    },
                    "min_episodes_per_week": {
                      "description": "Only podcasts publishing at least this many episodes per week on average (e.g. 5 for weekday dailies). Cadence is measured over the trailing 90 days; podcasts tracked too briefly to measure are excluded.",
                      "format": "double",
                      "type": "number"
                    },
                    "popularity_threshold": {
                      "description": "Restrict results to podcasts whose global popularity percentile is at least this value (accepted range [0,1]). Omitting the parameter or passing 0 disables the filter; only a value greater than 0 activates it. Popularity is always global — a cume_dist ranking over all currently-charting podcasts (Apple Podcasts) — never scoped to topic_id or any other filter. When the filter is active (threshold > 0), podcasts not currently charting have no percentile and are excluded, so a high threshold combined with a narrow topic_id may return zero results; lower or remove the threshold to widen the set.",
                      "format": "double",
                      "type": "number"
                    },
                    "publishing_status": {
                      "description": "Filter by publishing activity: active shows have released an episode within the last 90 days; dormant shows have not.",
                      "enum": [
                        "active",
                        "dormant"
                      ],
                      "type": "string"
                    },
                    "q": {
                      "description": "Search the catalog by podcast name. GET /v1/podcasts/search is the canonical search endpoint and accepts the same parameters. The search is forgiving: it handles typos, missing or extra words ('offline jon favreau' finds Offline with Jon Favreau), a name plus qualifiers ('equity techcrunch'), and pasted episode titles ('Ferrari | Acquired' finds Acquired). The best matches come first, and each result's match_quality tells you how confident the match is — including when a show matched only through its description (match_quality=description) rather than its name.",
                      "type": "string"
                    },
                    "slug": {
                      "description": "Filter by exact podcast slug (e.g., 'all-in'). Slugs are stable, human-readable identifiers returned on every podcast object.",
                      "type": "string"
                    },
                    "sort": {
                      "description": "Result ordering. relevance — the default whenever q is present — ranks by how well each podcast matches the query, breaking ties by popularity. popularity orders purely by the global popularity percentile (most popular first; podcasts not currently charting sort last), and also overrides topic_id's concentration ordering. Without q or topic_id, results are popularity-ordered either way.",
                      "enum": [
                        "relevance",
                        "popularity"
                      ],
                      "type": "string"
                    },
                    "suitability_tier": {
                      "description": "Filter by brand-suitability tier (IAB Tech Lab Brand Safety & Suitability Framework, formerly GARM). Only returns podcasts whose most recent suitability analysis assigned this tier. Podcasts without a suitability analysis are excluded when this filter is set.",
                      "enum": [
                        "SAFE",
                        "LIMITED",
                        "SENSITIVE",
                        "UNSAFE"
                      ],
                      "type": "string"
                    },
                    "topic_id": {
                      "description": "Filter by topic ID, ancestry slug (e.g., technology/artificial-intelligence), or ancestry path hash. Matches podcasts where the topic accounts for at least 20% of the show's episodes, ranked by topic concentration — not merely podcasts that mention it once.",
                      "type": "string"
                    }
                  },
                  "type": "object"
                },
                "type": {
                  "const": "http",
                  "type": "string"
                }
              },
              "required": [
                "type",
                "method"
              ],
              "type": "object"
            }
          },
          "required": [
            "input"
          ],
          "type": "object"
        }
      }
    },
    "lastUpdated": "2026-10-01T11:45:37.636Z",
    "quality": {
      "l30DaysTotalCalls": 2,
      "l30DaysUniquePayers": 1,
      "lastCalledAt": "2026-10-01T11:45:37.458Z"
    },
    "resource": "https://api.particle.pro/v1/podcasts",
    "serviceName": "Particle Pro",
    "tags": [
      "podcasts",
      "media intelligence",
      "particle pro"
    ],
    "type": "http",
    "x402Version": 2
  },
  "source": "x402_bazaar",
  "summary": "List and search podcasts. Returns a paginated list of podcasts, with filters for topic, language, suitability tier, popularity, and format."
}

What the leaf hashes

{"body":"bf728dd6440bae1e1db66f722518ef75e7b7ce21a414405cb876a07eaa111d3a","id":67966,"kind":"listing","method":"baseline/1","observed_us":1793025465468272,"prev":null,"subject":"x402_bazaar:https://api.particle.pro/v1/podcasts","subject_kind":"source_record"}

Proof

Fold these into the leaf in order, hashing each sorted pair with keccak256, to reach the root of 2026-10-26 (296695 rows).

1. 0xb36f41deac28132ec93a08595729a8289da03871daeb2d35d8586953a4795d72
2. 0x7b81c7898caba5019792e0e08da69b6f68c8183c4826e2c640214dbd476a9b28
3. 0x9367ca0e8879db55e55a74aeab0d8cc80a0928df5cafc5ffd996abcdc883a609
4. 0x12704dc30d326606c9c1a430f5461cd73b3c0d216c0884d1bf1b28589c44b052
5. 0x811e9af498f231f20a963543046d0a53bca03f9bca4b0d398052abd7e8ea8add
6. 0xf101be262cc6892b104b811a33484b9dc89f522369b75c1b69ad8d15f20d2540
7. 0xcf5653886f9a42b3936b010e7b90f39e45a0606197fa4c7b50a9880375749e42
8. 0x5774743e1b12c5d3f8139c1d8ac4b5c5d4bd4f2ca376c2ccb45e86abbc2e8996
9. 0x6c5fd3e671e37d3f9560c2d2b5d85a5fadbba4d2574ffde5cdcb68bdc9e07836
10. 0x02f72c34cadc7e4285efd87b76cb403220f4a25cdad402e412233c0a44206107
11. 0xc50bb1c2185da1e4294f4829be5412051ce30550dd05a2a26962841b3ba2399d
12. 0x3d6ec9d5ef8daa604601742088e213da0a439db6eff6ce50ec3ffb264a60ddd3
13. 0x3b1c0e225d1b1cb24cd5d5ea4af2de20ed68a1eaf8b61924ed1b81e4b9cf7e39
14. 0x083427e39db4dd470662401f6db5db8fadf084fc4274cf8621b368416952b78b
15. 0x1a74ed3b3756b9cd946da49701bcec120ec88645013da99fa9eea60b39e1a570
16. 0x123ec8bee20ddc55223eeef5a4f4d6c4b6416515adbb911c56759f5cde56e452
17. 0xd0651cb9bc8155eb52b5247d506e74b8a935057dc190ba52091702ac25ed3a40
18. 0x9a9024edb5069d88a324facb310a5ce8e495214bbaa968f077bede437390194f
19. 0x9b9ce5b74b9bab5121612ef6b64920a8d453cbf311096a423eef9702747e868a

Day root

0xf43e8dcc3d451a4788b26be904c55e8c4c0fa75c9666796c51db38d37e2c0df8

Chained

0x702d5ac508f08b0d1accf36af25822d8e5660367494edd17a642fb61e158a57a

Published

On Arc Testnet, block 69251483: 0x495162f8936e19f0039918feebe6c307f327cd6bf8c37219620b1970041fa9ae