# Research Grant Spending — String Normalisation + Two-Measure Correlation

> Research Grant Spending — String Normalisation + Two-Measure Correlation is a paid API for AI agents from market.datapackvibe.com, paid per call via x402, $0.01/call, status unknown (last checked 2026-10-22).

Performs string normalisation and two-measure correlation analysis on research grant spending records (budget_amount, spend_amount) for up to 200 rows, returning two independent analytical reports.

## Facts

- Endpoint: POST https://market.datapackvibe.com/x402/assistant-ib26-education-20-033?utm_source=zero.xyz
- Price: $0.01/call
- Payment: x402
- Status: unknown
- Last checked: 2026-10-22
- Activations on Zero: 0
- Tags: x402
- Canonical page: https://www.zero.xyz/c/research-grant-spending-string-normalisation-two-measure-correlation-f6810204
- Structured record (JSON): https://api.zero.xyz/v1/capabilities/cap_5671s-2IYRJFAGGB42DyE

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-grant-spending-string-normalisation-two-measure-correlation-f6810204 -d '<json body>'
```

Example prompt: Can you normalize the course group strings and run a correlation analysis between budget_amount and spend_amount for these research grant spending records? I have up to 50 rows with fields like row_id, course_group, date, budget_amount, and spend_amount — I need both reports in one call.

## When to prefer this

Choose this endpoint when you have tabular research grant spending data with course group labels and need both string/label normalisation and a budget-vs-spend correlation analysis in a single low-cost call. It is best suited for offline or batch analytical workflows on up to 200 rows where no live data lookup, prediction, or external action is required. At $0.01 USDC for two reports, it is cost-effective for lightweight education finance analytics.

## Known failure modes

- Submitting more than 200 rows returns a validation error
- Missing required fields (row_id, date, budget_amount, spend_amount) cause row-level rejection
- Malformed date strings not matching YYYY-MM-DD pattern fail schema validation
- Null values for both budget_amount and spend_amount in a row may reduce correlation reliability
- Empty rows array (minItems:1 violated) returns a schema error
- Values outside ±1,000,000,000,000 range are rejected by schema

## How this service works

Research grant spending — String normalisation + Two-measure correlation: String normalisation + Two-measure correlation for supplied research grant spending records (budget_amount, spend_amount). 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 string normalisation report covering the course_group field across all submitted rows, and (2) a two-measure correlation report quantifying the statistical relationship between budget_amount and spend_amount across the dataset. No external lookups or predictions are made; all analysis uses local analytical engines on the supplied data.

## Request schema (JSON Schema)

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

## More

- Live health (JSON, refreshed every minute): https://www.zero.xyz/c/research-grant-spending-string-normalisation-two-measure-correlation-f6810204/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)