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Forecast Verification — Secondary-Measure Weighted Mean & Keyed Dataset Comparison
x402
Forecast Verification — Secondary-Measure Weighted Mean & Keyed Dataset Comparison is a paid API for AI agents from market.datapackvibe.com, paid per call via x402, $0.01/call, status unknown (last checked 2026-10-26).
Computes a secondary-measure weighted mean and performs keyed dataset comparison on up to 200 rows of forecast vs. observed values, returning 2 analytical reports per call.
Price / call$0.01
Success—
StatusUnknown
How this service works
Forecast verification inputs — Secondary-measure weighted mean + Keyed dataset comparison: Secondary-measure weighted mean + Keyed dataset comparison for supplied forecast verification inputs records (forecast_value, observed_value). Up to 200 rows; 2 independent reports using shared local analytical engines. No live lookup, prediction, professional assessment or external action. 0.01 USDC includes 2 supplied-data reports for up to 200 rows.
Output
Returns 2 analytical reports per call: (1) a secondary-measure weighted mean computed over the selected field (forecast_value or observed_value) across the supplied rows, and (2) a keyed dataset comparison between the primary rows dataset and the reference 'other' dataset, identifying differences by row key. No external data is fetched; all analysis is performed on the submitted data.
Example use cases
Weather model accuracy audit
“I have 150 rows of daily weather station data with forecast_value and observed_value for October 2026 across two station groups — run a secondary-measure weighted mean on the forecast_value field and compare this dataset against last month's records so I can see where the model drifted.”
Station group forecast comparison
“Compare these two batches of forecast verification records from station groups A and B — I want the weighted mean of forecast_value and a keyed comparison between the two datasets to see which group has better forecast accuracy.”
Forecast bias detection across dates
“I've got two sets of 80 forecast-vs-observed records from different model runs, both keyed by row_id and date — give me the secondary-measure weighted mean and a side-by-side keyed dataset comparison so I can spot any systematic bias.”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-ib26-weather-24-186?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you need both a weighted mean statistic and a keyed row-level comparison between two forecast verification datasets in a single call. It is purpose-built for forecast vs. observed value analysis with station group context, supports up to 200 rows, and returns two distinct reports for $0.01 USDC. Prefer alternatives if you need live forecast data, external weather lookups, or more than 200 rows per batch.
Side effects
- Fewer than 1 row submitted — validation error
- More than 200 rows submitted — rejected with max-items error
- Missing required fields (row_id, date, forecast_value, observed_value) — schema validation failure
- Invalid date format (not YYYY-MM-DD) — pattern validation error
- Null values in forecast_value or observed_value may affect weighted mean computation
- Mismatched row_ids between primary and 'other' datasets reduce comparison coverage
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| rows | array | |
| field | string | |
| other | array |
Tags
x402
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