# Label Review Analytics: Exact Row Deduplication + IQR Outlier Flags

> Label Review Analytics: Exact Row Deduplication + IQR Outlier Flags is a paid API for AI agents from market.datapackvibe.com, paid per call via x402, $0.01/call, status unknown (last checked 2026-10-15).

Deduplicates exact rows and flags IQR-based outliers in label review records containing reviewed_records and changed_labels fields, producing two independent analytical reports.

## Facts

- Endpoint: POST https://market.datapackvibe.com/x402/assistant-ib26-analytics-12-049?utm_source=zero.xyz
- Price: $0.01/call
- Payment: x402
- Status: unknown
- Last checked: 2026-10-15
- Activations on Zero: 0
- Tags: x402
- Canonical page: https://www.zero.xyz/c/label-review-analytics-exact-row-deduplication-iqr-outlier-flags-8e7dced5
- Structured record (JSON): https://api.zero.xyz/v1/capabilities/cap_XJYtCVXJpaIYOhMwGqpsk

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-exact-row-deduplication-iqr-outlier-flags-8e7dced5 -d '<json body>'
```

Example prompt: Can you run deduplication and IQR outlier detection on my label review records? Here are up to 200 rows with fields like row_id, dataset_group, date, reviewed_records, and changed_labels — I want both reports, and check outliers on the reviewed_records field.

## When to prefer this

Choose this endpoint when you need fast, local, self-contained data quality checks on label review records specifically involving reviewed_records and changed_labels metrics. It is ideal for MLOps and annotation pipeline workflows where you want both deduplication and outlier detection in a single call without sending data to an external prediction or enrichment service. Prefer this over general-purpose analytics APIs when your dataset is under 200 rows and you need deterministic, reproducible results with no side effects.

## Known failure modes

- Input exceeds 200 rows — request will be rejected or truncated
- Missing required fields (row_id, dataset_group, date, reviewed_records, or changed_labels) cause validation errors
- Null numeric values in the target field may reduce outlier detection accuracy
- Invalid date format (not YYYY-MM-DD) triggers schema validation failure
- Insufficient data points for meaningful IQR calculation (very small row counts)

## How this service works

Label review — Exact row deduplication + IQR outlier flags: Exact row deduplication + IQR outlier flags 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) an exact row deduplication report identifying which rows are exact duplicates across all fields, and (2) an IQR outlier flags report identifying which rows have values in the selected field (reviewed_records or changed_labels) that fall outside the interquartile range bounds. Both reports are derived locally from the supplied data with no external lookups.

## 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-exact-row-deduplication-iqr-outlier-flags-8e7dced5/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)