# Label Review Analytics: String Normalisation + Secondary-Measure Weighted Mean

> Label Review Analytics: String Normalisation + Secondary-Measure Weighted Mean is a paid API for AI agents from market.datapackvibe.com, paid per call via x402, $0.01/call, status unknown (last checked 2026-11-03).

Computes string normalisation and secondary-measure weighted mean analytics on up to 200 label review records (reviewed_records, changed_labels), returning two independent analytical reports.

## Facts

- Endpoint: POST https://market.datapackvibe.com/x402/assistant-ib26-analytics-12-034?utm_source=zero.xyz
- Price: $0.01/call
- Payment: x402
- Status: unknown
- Last checked: 2026-11-03
- Activations on Zero: 0
- Tags: x402
- Canonical page: https://www.zero.xyz/c/label-review-analytics-string-normalisation-secondary-measure-ad9fb343
- Structured record (JSON): https://api.zero.xyz/v1/capabilities/cap_mq8CneESNeDwyZ1VAEeDx

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-string-normalisation-secondary-measure-ad9fb343 -d '<json body>'
```

Example prompt: Can you run string normalisation and weighted mean analytics on my label review data? I have 4 rows: row-1 on 2026-10-01 in group-a with 10 reviewed_records and 1 changed_label, row-2 on 2026-10-02 in group-b with 20 reviewed_records and 2 changed_labels, row-3 on 2026-10-03 in group-a with 15 reviewed_records and 3 changed_labels, and row-4 on 2026-10-04 in group-b with 30 reviewed_records and 4 changed_labels — use reviewed_records as the primary field.

## When to prefer this

Choose this endpoint when you need both string normalisation and weighted mean analytics on label review data in a single call, without requiring live data lookup, external predictions, or real-time data sources. It is ideal for offline batch analysis of ML labelling pipelines, data quality audits, and label change rate summarisation across dataset groups, particularly when cost efficiency (two reports for $0.01 USDC) and local computation without side effects are priorities.

## Known failure modes

- More than 200 rows submitted — request will be rejected or truncated
- Missing required fields (row_id, date, reviewed_records, changed_labels) cause validation errors
- Invalid date format (not YYYY-MM-DD) causes schema rejection
- Null values for both reviewed_records and changed_labels may produce undefined weighted mean
- Numbers outside allowed range (±1,000,000,000,000) cause validation failure

## How this service works

Label review — String normalisation + Secondary-measure weighted mean: String normalisation + Secondary-measure weighted mean 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

Two independent analytical reports: (1) a string normalisation report over the supplied label review records, and (2) a secondary-measure weighted mean report computed across the reviewed_records and changed_labels fields, scoped to up to 200 input rows across specified dataset groups and dates.

## 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-string-normalisation-secondary-measure-ad9fb343/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)