# Duplicate Observations — Base-100 Series + IQR Outlier Flags

> Duplicate Observations — Base-100 Series + 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 2026-10-18).

Computes a Base-100 indexed time series and IQR-based outlier flags for duplicate_rows and total_rows metrics across up to 200 supplied data records.

## Facts

- Endpoint: POST https://market.datapackvibe.com/x402/assistant-ib26-analytics-04-164?utm_source=zero.xyz
- Price: $0.01/call
- Payment: x402
- Status: unknown
- Last checked: 2026-10-18
- Activations on Zero: 0
- Tags: x402
- Canonical page: https://www.zero.xyz/c/duplicate-observations-base-100-series-iqr-outlier-flags-d079d5f4
- Structured record (JSON): https://api.zero.xyz/v1/capabilities/cap_j-wi5JYaw-cIBmiawKB-n

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 duplicate-observations-base-100-series-iqr-outlier-flags-d079d5f4 -d '<json body>'
```

Example prompt: Can you run the base-100 indexing and IQR outlier detection on my duplicate observation data? I have 4 records across groups 'group-a' and 'group-b' from 2026-10-01 to 2026-10-04, analyzing the duplicate_rows field starting from base index 0.

## When to prefer this

Choose this endpoint when you have pre-collected duplicate observation records (up to 200 rows) with date, group, duplicate_rows, and total_rows fields and need both a normalized trend view (Base-100) and statistical outlier detection (IQR) in a single low-cost call. It is ideal for data quality monitoring workflows, ingestion pipeline audits, and time series comparison across dataset groups where no external data, live lookups, or predictions are needed.

## Known failure modes

- Fewer than 1 row supplied — minItems validation failure
- More than 200 rows supplied — maxItems exceeded
- Missing required fields (row_id, dataset_group, date, duplicate_rows, total_rows) — schema validation error
- Invalid date format (not YYYY-MM-DD) — pattern mismatch
- base_index out of range (must be 0–199 and within row count) — validation error
- All values null or identical — IQR computation may produce degenerate results
- Payment not included or insufficient — x402 payment required error

## How this service works

Duplicate observations — Base-100 series + IQR outlier flags: Base-100 series + IQR outlier flags for supplied duplicate observations records (duplicate_rows, total_rows). 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 Base-100 normalized time series for the selected field (duplicate_rows or total_rows) anchored to the specified base_index record, and (2) IQR-based outlier flags identifying which records fall outside the interquartile range — both computed 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",
     "duplicate_rows",
     "total_rows"
    ],
    "properties": {
     "date": {
      "type": "string",
      "default": "",
      "pattern": "^\\d{4}-\\d{2}-\\d{2}$",
      "maxLength": 10
     },
     "row_id": {
      "type": "string",
      "default": "",
      "maxLength": 80,
      "minLength": 1
     },
     "total_rows": {
      "type": [
       "number",
       "null"
      ],
      "maximum": 1000000000000,
      "minimum": -1000000000000
     },
     "dataset_group": {
      "type": "string",
      "default": "",
      "maxLength": 80
     },
     "duplicate_rows": {
      "type": [
       "number",
       "null"
      ],
      "maximum": 1000000000000,
      "minimum": -1000000000000
     }
    },
    "additionalProperties": false
   },
   "default": [
    {
     "date": "2026-10-01",
     "row_id": "row-1",
     "total_rows": 1,
     "dataset_group": "group-a",
     "duplicate_rows": 10
    },
    {
     "date": "2026-10-02",
     "row_id": "row-2",
     "total_rows": 2,
     "dataset_group": "group-b",
     "duplicate_rows": 20
    },
    {
     "date": "2026-10-03",
     "row_id": "row-3",
     "total_rows": 3,
     "dataset_group": "group-a",
     "duplicate_rows": 15
    },
    {
     "date": "2026-10-04",
     "row_id": "row-4",
     "total_rows": 4,
     "dataset_group": "group-b",
     "duplicate_rows": 30
    }
   ],
   "maxItems": 200,
   "minItems": 1
  },
  "field": {
   "enum": [
    "duplicate_rows",
    "total_rows"
   ],
   "type": "string",
   "default": "duplicate_rows"
  },
  "base_index": {
   "type": "integer",
   "default": 0,
   "maximum": 199,
   "minimum": 0
  }
 }
}
```

## More

- Live health (JSON, refreshed every minute): https://www.zero.xyz/c/duplicate-observations-base-100-series-iqr-outlier-flags-d079d5f4/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)