# Label Review Analytics — Base-100 Series + Two-Measure Correlation

> Label Review Analytics — Base-100 Series + Two-Measure Correlation is a paid API for AI agents from market.datapackvibe.com, paid per call via x402, $0.01/call, status unknown (last checked 2026-10-24).

Computes a Base-100 index series and a two-measure Pearson/correlation report for label review data (reviewed_records and changed_labels) across up to 200 rows, using local analytical engines with no external lookups.

## Facts

- Endpoint: POST https://market.datapackvibe.com/x402/assistant-ib26-analytics-12-165?utm_source=zero.xyz
- Price: $0.01/call
- Payment: x402
- Status: unknown
- Last checked: 2026-10-24
- Activations on Zero: 0
- Tags: x402
- Canonical page: https://www.zero.xyz/c/label-review-analytics-base-100-series-two-measure-correlation-3d54af30
- Structured record (JSON): https://api.zero.xyz/v1/capabilities/cap_a7h48UuLJdLAxqS8nAsvd

Status and success rate cover calls made through Zero and Zero's own probes. Third-party monitors may report differently.

## How to call it through Zero

Zero handles the 402 payment challenge and records the run. With the Zero CLI installed (`npm i -g @zeroxyz/cli`):

```sh
zero fetch --capability label-review-analytics-base-100-series-two-measure-correlation-3d54af30 -d '<json body>'
```

Example prompt: I have 4 rows of label review data — on 2026-10-01 group-a had 10 reviewed records and 1 changed label, 2026-10-02 group-b had 20 reviewed and 2 changed, 2026-10-03 group-a had 15 reviewed and 3 changed, 2026-10-04 group-b had 30 reviewed and 4 changed — can you run a Base-100 index series using reviewed_records starting from row index 0, and also give me the two-measure correlation between reviewed_records and changed_labels?

## When to prefer this

Choose this endpoint when you have label review tabular data (reviewed_records, changed_labels) and need both a normalized Base-100 trend series and a two-measure correlation in a single low-cost call. It is ideal for ML annotation teams, data QA pipelines, and labeling ops analysts who want local, offline-style analytics without sending data to a prediction service or external enrichment API. It is not appropriate for real-time lookups, forecasting, large datasets exceeding 200 rows, or use cases requiring professional statistical assessment or live data ingestion.

## Known failure modes

- Empty or missing rows array returns a validation error
- More than 200 rows submitted exceeds the maxItems limit and is rejected
- Invalid date format (not YYYY-MM-DD) causes schema validation failure
- base_index out of range (>=number of rows) causes computation error
- null values in both reviewed_records and changed_labels may produce degenerate correlation output
- Non-numeric values in numeric fields are rejected by schema validation
- Payment failure returns HTTP 402 and no computation is performed

## How this service works

Label review — Base-100 series + Two-measure correlation: Base-100 series + Two-measure correlation for supplied label review records (reviewed_records, changed_labels). 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 two analytical reports: (1) a Base-100 index series for the chosen field (reviewed_records or changed_labels) anchored at the specified base_index row, showing each row's value normalized relative to that baseline; and (2) a two-measure correlation report quantifying the statistical relationship between reviewed_records and changed_labels across all supplied rows. Both reports are computed locally with no external data enrichment.

## Request schema (JSON Schema)

```json
{
 "type": "object",
 "properties": {
  "rows": {
   "type": "array",
   "items": {
    "type": "object",
    "required": [
     "row_id",
     "dataset_group",
     "date",
     "reviewed_records",
     "changed_labels"
    ],
    "properties": {
     "date": {
      "type": "string",
      "default": "",
      "pattern": "^\\d{4}-\\d{2}-\\d{2}$",
      "maxLength": 10
     },
     "row_id": {
      "type": "string",
      "default": "",
      "maxLength": 80,
      "minLength": 1
     },
     "dataset_group": {
      "type": "string",
      "default": "",
      "maxLength": 80
     },
     "changed_labels": {
      "type": [
       "number",
       "null"
      ],
      "maximum": 1000000000000,
      "minimum": -1000000000000
     },
     "reviewed_records": {
      "type": [
       "number",
       "null"
      ],
      "maximum": 1000000000000,
      "minimum": -1000000000000
     }
    },
    "additionalProperties": false
   },
   "default": [
    {
     "date": "2026-10-01",
     "row_id": "row-1",
     "dataset_group": "group-a",
     "changed_labels": 1,
     "reviewed_records": 10
    },
    {
     "date": "2026-10-02",
     "row_id": "row-2",
     "dataset_group": "group-b",
     "changed_labels": 2,
     "reviewed_records": 20
    },
    {
     "date": "2026-10-03",
     "row_id": "row-3",
     "dataset_group": "group-a",
     "changed_labels": 3,
     "reviewed_records": 15
    },
    {
     "date": "2026-10-04",
     "row_id": "row-4",
     "dataset_group": "group-b",
     "changed_labels": 4,
     "reviewed_records": 30
    }
   ],
   "maxItems": 200,
   "minItems": 1
  },
  "field": {
   "enum": [
    "reviewed_records",
    "changed_labels"
   ],
   "type": "string",
   "default": "reviewed_records"
  },
  "base_index": {
   "type": "integer",
   "default": 0,
   "maximum": 199,
   "minimum": 0
  }
 }
}
```

## More

- Live health (JSON, refreshed every minute): https://www.zero.xyz/c/label-review-analytics-base-100-series-two-measure-correlation-3d54af30/health.json
- [Zero catalog index](https://www.zero.xyz/llms.txt)
- [Other services from market.datapackvibe.com](https://www.zero.xyz/host/market.datapackvibe.com/llms.txt)