# Label Review Analytics: Numeric Row Ordering + Two-Measure Correlation

> Label Review Analytics: Numeric Row Ordering + 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).

Runs two analytical reports on label review data — numeric row ordering and correlation between reviewed_records and changed_labels — for up to 200 supplied rows.

## Facts

- Endpoint: POST https://market.datapackvibe.com/x402/assistant-ib26-analytics-12-120?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-numeric-row-ordering-two-measure-correlation-63692b89
- Structured record (JSON): https://api.zero.xyz/v1/capabilities/cap_KjAwjowAYwwfz8GQe6Ds8

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-numeric-row-ordering-two-measure-correlation-63692b89 -d '<json body>'
```

Example prompt: I have label review data across two groups for October 2026 — can you run the numeric row ordering and two-measure correlation reports on it, using reviewed_records as the primary field? I'll supply up to 10 rows with row_id, date, dataset_group, reviewed_records, and changed_labels.

## When to prefer this

Choose this endpoint when you have label review tabular data with reviewed_records and changed_labels fields and need both a numeric ordering and a correlation analysis in a single low-cost call. Ideal for ML ops teams auditing annotation pipelines, data quality analysts reviewing labeling throughput, or anyone needing offline statistical analysis on up to 200 rows of label review records without external data enrichment or live predictions.

## Known failure modes

- More than 200 rows submitted — request will be rejected
- Missing required fields (row_id, date, reviewed_records, changed_labels) on any row
- Date field not in YYYY-MM-DD format
- Numeric values outside the allowed range (-1e12 to 1e12)
- Empty rows array submitted
- Insufficient variation in data for meaningful correlation (e.g. all values identical)

## How this service works

Label review — Numeric row ordering + Two-measure correlation: Numeric row ordering + 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 independent analytical reports: (1) a numeric ordering of the supplied rows based on the selected field (reviewed_records or changed_labels), and (2) a two-measure correlation report quantifying the statistical relationship between reviewed_records and changed_labels across the submitted rows. No external lookups or predictions are made — all analysis is performed on the supplied data.

## 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"
  }
 }
}
```

## More

- Live health (JSON, refreshed every minute): https://www.zero.xyz/c/label-review-analytics-numeric-row-ordering-two-measure-correlation-63692b89/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)