hubvibe-io.com

{
  "$schema": "https://json-schema.org/draft/2020-12/schema",
  "description": "The 200 body of every paid /work call. `result` is the worker's own output (its schema is per route); everything else is the same on every /work route. A receipt for the job is at `receipt_url`.",
  "properties": {
    "attribution": {
      "$ref": "#/components/schemas/Attribution"
    },
    "billing_warning": {
      "description": "Present only when the charge was recorded with a caveat.",
      "examples": [
        "settlement pending"
      ],
      "type": "string"
    },
    "price_usd": {
      "description": "What this call cost, in USD.",
      "examples": [
        0.02
      ],
      "type": "number"
    },
    "provenance": {
      "$ref": "#/components/schemas/Provenance"
    },
    "receipt_id": {
      "description": "Receipt id for this job.",
      "examples": [
        "rcpt_9f1c2b3a4d5e6f70"
      ],
      "type": "string"
    },
    "receipt_url": {
      "description": "Where to fetch the machine-readable receipt (free, no payment).",
      "examples": [
        "/work/receipts/rcpt_9f1c2b3a4d5e6f70"
      ],
      "type": "string"
    },
    "result": {
      "properties": {
        "anomaly_count": {
          "description": "Rows flagged as anomalies at the threshold.",
          "examples": [
            2
          ],
          "type": "integer"
        },
        "anomaly_prob_threshold": {
          "description": "Probability threshold used.",
          "examples": [
            0.95
          ],
          "type": "number"
        },
        "columns": {
          "description": "AI.DETECT_ANOMALIES output columns.",
          "examples": [
            [
              "state_name",
              "date",
              "confirmed_cases",
              "is_anomaly",
              "lower_bound",
              "upper_bound",
              "anomaly_probability"
            ]
          ],
          "items": {
            "description": "AI.DETECT_ANOMALIES output column.",
            "examples": [
              "is_anomaly"
            ],
            "type": "string"
          },
          "type": "array"
        },
        "data_col": {
          "description": "Value column.",
          "examples": [
            "confirmed_cases"
          ],
          "type": "string"
        },
        "gib_processed": {
          "description": "Gibibytes BigQuery scanned; the metered cost basis.",
          "examples": [
            0.012
          ],
          "type": "number"
        },
        "history_table": {
          "description": "Table the forecast is fitted on.",
          "examples": [
            "bigquery-public-data.covid19_nyt.us_states"
          ],
          "type": "string"
        },
        "mode": {
          "description": "split_by_time: one table, its latest periods scored against the rest; two_tables: target scored against history.",
          "enum": [
            "split_by_time",
            "two_tables"
          ],
          "examples": [
            "split_by_time"
          ],
          "type": "string"
        },
        "row_count": {
          "description": "Rows returned.",
          "examples": [
            10
          ],
          "type": "integer"
        },
        "rows": {
          "description": "Checked rows with their anomaly flag.",
          "examples": [
            [
              {
                "anomaly_probability": "0.12",
                "confirmed_cases": "8631000",
                "date": "2023-03-20",
                "is_anomaly": "false",
                "state_name": "Texas"
              }
            ]
          ],
          "items": {
            "additionalProperties": true,
            "description": "One checked point.",
            "examples": [
              {
                "anomaly_probability": "0.12",
                "confirmed_cases": "8631000",
                "date": "2023-03-20",
                "is_anomaly": "false",
                "state_name": "Texas"
              }
            ],
            "properties": {},
            "required": [],
            "type": "object"
          },
          "type": "array"
        },
        "target_periods": {
          "description": "Latest timestamps scored in split_by_time mode; null for two tables.",
          "examples": [
            30
          ],
          "type": [
            "integer",
            "null"
          ]
        },
        "target_table": {
          "description": "Table checked for anomalies.",
          "examples": [
            "bigquery-public-data.covid19_nyt.us_states"
          ],
          "type": "string"
        },
        "timestamp_col": {
          "description": "Timestamp column.",
          "examples": [
            "date"
          ],
          "type": "string"
        }
      },
      "required": [
        "history_table",
        "target_table",
        "timestamp_col",
        "data_col",
        "anomaly_prob_threshold",
        "mode",
        "target_periods",
        "columns",
        "rows",
        "row_count",
        "anomaly_count",
        "gib_processed"
      ],
      "type": "object"
    },
    "status": {
      "const": "ok",
      "description": "Present only on a delivered result.",
      "type": "string"
    },
    "worker": {
      "description": "Catalog name of the worker that ran.",
      "examples": [
        "market.quote"
      ],
      "type": "string"
    }
  },
  "required": [
    "status",
    "worker",
    "price_usd",
    "result",
    "provenance",
    "receipt_id",
    "receipt_url"
  ],
  "title": "data.anomalies response",
  "type": "object"
}