# Research Sample Recovery – IQR Outlier Flags

> Research Sample Recovery – 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 2026-10-16).

Applies interquartile range (IQR) outlier detection to research sample recovery mass data, flagging anomalous records among up to 200 supplied specimen rows.

## Facts

- Endpoint: POST https://market.datapackvibe.com/x402/assistant-ar-analytics-sample-recovery-outliers?utm_source=zero.xyz
- Price: $0.01/call
- Payment: x402
- Status: unknown
- Last checked: 2026-10-16
- Activations on Zero: 0
- Tags: x402
- Canonical page: https://www.zero.xyz/c/research-sample-recovery-iqr-outlier-flags-d7dcda42
- Structured record (JSON): https://api.zero.xyz/v1/capabilities/cap_ZrWKDKdnvrSmD_BZ5qn1O

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 research-sample-recovery-iqr-outlier-flags-d7dcda42 -d '<json body>'
```

Example prompt: I have 15 specimen recovery records with dates, input masses, and recovered masses — can you run an IQR outlier analysis on the recovered_mass_g field and tell me which rows are flagged as anomalies?

## When to prefer this

Choose this endpoint when you have up to 200 labeled specimen recovery records and need a fast, local IQR-based outlier flag report with no external data enrichment. It is ideal for lab QC pipelines, pre-analysis data cleaning, and research workflows where you want to identify anomalous mass measurements without sending data to an external ML or forecasting service. Prefer alternatives if you need forecasting, trend analysis, or outlier detection on non-mass fields beyond this schema.

## Known failure modes

- Fewer than 1 row submitted 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
- Missing required fields (row_id, input_mass_g, or recovered_mass_g) cause per-row rejection
- All-null values in the selected field may produce undefined IQR bounds
- Non-numeric mass values cause type validation errors
- Payment not included or insufficient USDC results in 402 Payment Required

## How this service works

Research sample recovery - IQR outlier flags: IQR outlier flags for Research sample recovery. Up to 200 supplied typed records. Local descriptive analytics; no enrichment or forecast. One of 25 new profiles across 20 shared operations in this industry. 0.01 USDC includes one bounded iqr outlier flags report.

## Output

A bounded IQR outlier flags report covering each submitted row, indicating which records fall outside the interquartile range for the selected mass field (input_mass_g or recovered_mass_g), along with the computed quartile boundaries used for flagging. No enrichment or forecasting is included — purely local descriptive analytics on the supplied data.

## Request schema (JSON Schema)

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

## More

- Live health (JSON, refreshed every minute): https://www.zero.xyz/c/research-sample-recovery-iqr-outlier-flags-d7dcda42/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)