# Scene Geometry Weighted Mean with Missing-Value Fill

> Scene Geometry Weighted Mean with Missing-Value Fill is a paid API for AI agents from market.datapackvibe.com, paid per call via x402, $0.01/call, status unknown (last checked 2026-10-21).

Computes a secondary-measure weighted mean for scene geometry data (object_count, triangle_count) and fills missing values using a chosen fill method, returning 2 analytical reports for up to 200 rows.

## Facts

- Endpoint: POST https://market.datapackvibe.com/x402/assistant-ib26-creative-05-187?utm_source=zero.xyz
- Price: $0.01/call
- Payment: x402
- Status: unknown
- Last checked: 2026-10-21
- Activations on Zero: 0
- Tags: x402
- Canonical page: https://www.zero.xyz/c/scene-geometry-weighted-mean-with-missing-value-fill-b92c846a
- Structured record (JSON): https://api.zero.xyz/v1/capabilities/cap_3cRTd_1CeMXhLWUZ4O5Ni

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 scene-geometry-weighted-mean-with-missing-value-fill-b92c846a -d '<json body>'
```

Example prompt: Can you compute the secondary-measure weighted mean for my scene geometry records and fill any missing object_count values using median imputation? I have about 50 rows across two asset groups — group-a and group-b — dated from 2026-10-01 to 2026-10-31.

## When to prefer this

Choose this endpoint when you need both weighted-mean aggregation and missing-value imputation for 3D scene geometry data (object_count, triangle_count) in a single call, especially when working with up to 200 rows and needing two analytical reports at low cost. Prefer this over general analytics tools when your data is specifically structured as scene geometry records with asset_group and date dimensions, and you want deterministic local computation with no external lookups.

## Known failure modes

- Input array exceeds 200 rows — request will be rejected
- Missing required fields (row_id, date, asset_group) cause validation errors
- Invalid date format (not YYYY-MM-DD) fails pattern validation
- All values in target field are null — weighted mean may be undefined
- Invalid enum value for field or method parameters returns schema error
- Payment of 0.01 USDC not completed causes 402 rejection

## How this service works

Scene geometry — Secondary-measure weighted mean + Explicit missing-value fill: Secondary-measure weighted mean + Explicit missing-value fill for supplied scene geometry records (object_count, triangle_count). 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 2 analytical reports containing: (1) a secondary-measure weighted mean of the specified field (object_count or triangle_count) across the supplied rows, and (2) the dataset with missing values filled using the chosen method (zero, mean, or median). Results are scoped to the submitted rows only — no external data is fetched.

## Request schema (JSON Schema)

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

## More

- Live health (JSON, refreshed every minute): https://www.zero.xyz/c/scene-geometry-weighted-mean-with-missing-value-fill-b92c846a/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)