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Evidence row 548177

Observed , by sync.x402_bazaar/1.

Kind
listing
About
source_record x402_bazaar:https://pjm-nowcast-production.up.railway.app/v1/spread/probability-card
Recorded
Previous row
#56123
Body SHA-256
a1112f4493fbc0809ae5c9c10dd0b14250ea85d3751fc41a4a01aa420c3ccc18
Leaf
0x8f2d3d157d4a450524595f724a04727d48e3520d4f76d43e600c5c8f9f01fb69

What was observed

{
  "endpoints": [
    [
      "x402",
      "https://pjm-nowcast-production.up.railway.app/v1/spread/probability-card"
    ]
  ],
  "name": "pjm-nowcast",
  "owner_address": "0x34cfb8bdbf16e4484b7da0ed31deed5771b16c8f",
  "raw": {
    "accepts": [
      {
        "amount": "250000",
        "asset": "0x833589fCD6eDb6E08f4c7C32D4f71b54bdA02913",
        "extra": {
          "name": "USD Coin",
          "version": "2"
        },
        "maxAmountRequired": "250000",
        "maxTimeoutSeconds": 60,
        "network": "eip155:8453",
        "payTo": "0x34cfb8bdbf16e4484b7da0ed31deed5771b16c8f",
        "price": "0.25",
        "scheme": "exact"
      },
      {
        "amount": "250000",
        "asset": "USDC",
        "maxAmountRequired": "250000",
        "maxTimeoutSeconds": 60,
        "network": "solana:5eykt4UsFv8P8NJdTREpY1vzqKqZKvdp",
        "payTo": "DCi9X5mmacNGLeJvCw9fdWgX3G8V4QquDn4EuXATkcYr",
        "price": "0.25",
        "scheme": "exact"
      }
    ],
    "description": "PJM zonal spread jump probability. empirical probability card for the evening congestion bar. whenToUse: next on-peak day or trailing congestion-season check. whenNotToUse: month-ahead, season-ahead, Black vol, a price forecast.",
    "extensions": {
      "bazaar": {
        "info": {
          "input": {
            "body": {
              "lookbackDays": 5
            },
            "bodyType": "json",
            "method": "POST",
            "type": "http"
          },
          "output": {
            "example": {
              "K": 12.4,
              "avgPayoff": 1.8,
              "hitRate": 0.4,
              "sample": {
                "dayCount": 5,
                "tag": "high-congestion-season"
              }
            },
            "type": "json"
          }
        },
        "schema": {
          "$schema": "https://json-schema.org/draft/2020-12/schema",
          "properties": {
            "input": {
              "additionalProperties": false,
              "properties": {
                "body": {
                  "additionalProperties": false,
                  "properties": {
                    "asOf": {
                      "description": "Optional ISO-8601 sample end. Default: now.",
                      "type": "string"
                    },
                    "lookbackDays": {
                      "default": 5,
                      "description": "Trailing on-peak EPT weekdays (skip weekends and NERC holidays). Default 5, max 30.",
                      "maximum": 30,
                      "minimum": 1,
                      "type": "integer"
                    }
                  },
                  "required": [
                    "lookbackDays"
                  ],
                  "type": "object"
                },
                "bodyType": {
                  "enum": [
                    "json",
                    "form-data",
                    "text"
                  ],
                  "type": "string"
                },
                "method": {
                  "enum": [
                    "POST",
                    "PUT",
                    "PATCH"
                  ],
                  "type": "string"
                },
                "type": {
                  "const": "http",
                  "type": "string"
                }
              },
              "required": [
                "type",
                "method",
                "bodyType",
                "body"
              ],
              "type": "object"
            },
            "output": {
              "properties": {
                "example": {
                  "description": "empirical probability card. Empirical only. Not a forecast, not a mid.",
                  "example": {
                    "K": 12.4,
                    "avgPayoff": 1.8,
                    "hitRate": 0.4,
                    "sample": {
                      "dayCount": 5,
                      "tag": "high-congestion-season"
                    }
                  },
                  "properties": {
                    "K": {
                      "type": "number"
                    },
                    "avgPayoff": {
                      "type": "number"
                    },
                    "buyerBeware": {
                      "type": "string"
                    },
                    "dailyMaxP50": {
                      "type": "number"
                    },
                    "dailyMaxP95": {
                      "type": "number"
                    },
                    "hitDays": {
                      "type": "integer"
                    },
                    "hitRate": {
                      "type": "number"
                    },
                    "latestCompleteDay": {
                      "type": "object"
                    },
                    "latestNowcast": {
                      "type": "object"
                    },
                    "sample": {
                      "properties": {
                        "dayCount": {
                          "type": "integer"
                        },
                        "firstEptDate": {
                          "type": "string"
                        },
                        "lastEptDate": {
                          "type": "string"
                        },
                        "tag": {
                          "const": "high-congestion-season",
                          "type": "string"
                        }
                      },
                      "type": "object"
                    }
                  },
                  "type": "object"
                },
                "type": {
                  "type": "string"
                }
              },
              "required": [
                "type"
              ],
              "type": "object"
            }
          },
          "required": [
            "input"
          ],
          "type": "object"
        }
      }
    },
    "lastUpdated": "2026-10-27T13:00:41.486Z",
    "quality": {
      "l30DaysTotalCalls": 4,
      "l30DaysUniquePayers": 1,
      "lastCalledAt": "2026-10-27T13:00:41.282Z"
    },
    "resource": "https://pjm-nowcast-production.up.railway.app/v1/spread/probability-card",
    "serviceName": "pjm-nowcast",
    "tags": [
      "pjm",
      "spread",
      "on-peak",
      "residual",
      "jump"
    ],
    "type": "http",
    "x402Version": 2
  },
  "source": "x402_bazaar",
  "summary": "PJM zonal spread jump probability. empirical probability card for the evening congestion bar. whenToUse: next on-peak day or trailing congestion-season check. whenNotToUse: month-ahead, season-ahead, Black vol, a price forecast."
}

What the leaf hashes

{"body":"a1112f4493fbc0809ae5c9c10dd0b14250ea85d3751fc41a4a01aa420c3ccc18","id":548177,"kind":"listing","method":"sync.x402_bazaar/1","observed_us":1793133280829094,"prev":56123,"subject":"x402_bazaar:https://pjm-nowcast-production.up.railway.app/v1/spread/probability-card","subject_kind":"source_record"}

Proof

Fold these into the leaf in order, hashing each sorted pair with keccak256, to reach the root of (273461 rows).

  1. 0x8f2d263b50ad622b407624640d6384e4b93224fe751a9c612f639ed325f0500f
  2. 0x32804f165af99fbf9a42ea162b49868b1533b10ec7cc35b69cae14f7639592ca
  3. 0x59c0c73709d93ba60e927b1744b501664838494319f715c3ccfc55d0f811230a
  4. 0x71543a6c9a31eeaad509b62af5b34c36c8bd6359a78b5ac34b639e32a68978c5
  5. 0xe3de807eeb730793a87bf1e82feca24e21db8d3dcc81712c99077e39cd9ac313
  6. 0x317ef36818b86d211ba5f6d6fe511139740782922c27672e9c7717252a57fa0e
  7. 0x290901cac4b9bfb4db38f61b25ebdd769f74e1f2a478ee68c2d8aeb654593e25
  8. 0xaf51226d63637b01f00cac1731409184d8160d5dd46ab76b43117d96a9b40bd2
  9. 0x6daacf365fdb91c42e4a00d0820b89e86f73b3d9d7fd5a39cca9973ec90ebc29
  10. 0x41d116872d35101e280e8ba654733ed9c35d9cf4f524fd91218920226c8aca68
  11. 0xbff43d30538b90ef025129e8a238dc8959481edca06b37ecee4c2be1f617127d
  12. 0x3d13b6f855471289691a683ee58cac14977b2531dabc14f9c666e928df0908e6
  13. 0x5c9cbca5bb1d6be4d84e301b4e4c1a280536eb16ee98ed4add9057142c132dde
  14. 0x06e3b43165f5b3c31d850bc32f20b2e25b844564c4e042c141b9748c26a5a600
  15. 0xb4f7223140c8a36cb87a63d77cf617086d9968dc4658f03e102571ebe06e9ed6
  16. 0xfecf3d4646dd4984a13dd715499e842c3fde63692336d97394c2bfd8e877ca5d
  17. 0xf30fddbf4811226c58e8f0daf36fddd79fc5f1356b592bb1d99a8061ddbabe66
  18. 0x2bf8151e5f157dd183b9de6fa00469551932a7a6e3f33a694895000ac9061197
  19. 0x9fc354c0ea3efc3f1b6548bb77ea902a50f2c9647647ea61592efce2bd795699
Day root
0xdd77e5e99da32c3f154180d63e3c3e6fe11e896a2c6896412ef6b5c4bcf7e795
Chained
0x23bb4dfd09f55c15ac3962f53578e02c6114d5bfd9bb451cf8794fb6e2817ef4
Published
On Arc Testnet, block 69414147: 0xb2ebd83aafeb765a0ce66e76aefb133ed06606c98038fd56191e2bcd1dcb77b4

How to check it · This row as JSON