# Maha Strategies Quantum Measurement Uncertainty — Binomial Shot-Count Statistics

> Maha Strategies Quantum Measurement Uncertainty — Binomial Shot-Count Statistics is a paid API for AI agents from www.mahastrategies.com, paid per call via x402, $0.012001/call, status unknown (last checked 2026-10-17).

Computes probabilities and binomial confidence intervals from shot-count arrays using a specified interval method and independence assumptions

## Facts

- Endpoint: POST https://www.mahastrategies.com/api/v1/micro/quantum-measurement-uncertainty?utm_source=zero.xyz
- Price: $0.012001/call
- Payment: x402
- Status: unknown
- Last checked: 2026-10-17
- Activations on Zero: 0
- Tags: x402
- Canonical page: https://www.zero.xyz/c/maha-strategies-quantum-measurement-uncertainty-binomial-shot-count-b50c8f2e
- Structured record (JSON): https://api.zero.xyz/v1/capabilities/cap_P3Rn1CZqlgFNQUaz053-5

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 maha-strategies-quantum-measurement-uncertainty-binomial-shot-count-b50c8f2e -d '<json body>'
```

Example prompt: I have shot-count results from a quantum measurement experiment — the counts array is [42, 58, 37, 63] and the data is synthetic. Can you compute the binomial probabilities and confidence intervals with independence assumptions for those counts?

## When to prefer this

Choose this endpoint when you have discrete shot-count arrays from quantum measurements or repeated binary trials and need statistically rigorous binomial probabilities with confidence intervals under independence assumptions. It is purpose-built for quantum measurement post-processing workflows where standard statistical libraries are not available inline, and where a compact, auditable per-call result with receipt digest is needed. Prefer it over generic statistics APIs when you need tight integration with the Maha microproduct receipt/audit trail.

## Known failure modes

- Invalid or empty counts array (below minItems:1 or above maxItems:32) returns a validation error
- Unrecognized dataClass value (must be 'public' or 'synthetic') causes schema rejection
- Missing required body fields (dataClass or counts) returns a 400-level error
- Non-integer or null values in counts array may fail schema validation
- Payment failure or insufficient USDC balance prevents endpoint execution

## How this service works

For agents reviewing shot-count results: return probabilities and binomial confidence intervals with the interval method and independence assumptions.

## Output

Returns a structured result object containing computed probabilities and binomial confidence interval boundaries for each supplied shot-count value, along with a version identifier, offer ID (quantum-measurement-uncertainty), input digest, amount in base units (12001), and a receipt digest for auditability.

## Request schema (JSON Schema)

```json
{
 "type": "object",
 "$schema": "https://json-schema.org/draft/2020-12/schema",
 "required": [
  "input"
 ],
 "properties": {
  "input": {
   "type": "object",
   "required": [
    "type",
    "method",
    "bodyType",
    "body"
   ],
   "properties": {
    "body": {
     "type": "object",
     "required": [
      "dataClass",
      "counts"
     ],
     "properties": {
      "counts": {
       "type": "array",
       "maxItems": 32,
       "minItems": 1
      },
      "dataClass": {
       "enum": [
        "public",
        "synthetic"
       ],
       "type": "string"
      }
     },
     "additionalProperties": false
    },
    "type": {
     "type": "string",
     "const": "http"
    },
    "method": {
     "enum": [
      "POST"
     ],
     "type": "string"
    },
    "bodyType": {
     "enum": [
      "json",
      "form-data",
      "text"
     ],
     "type": "string"
    }
   },
   "additionalProperties": false
  },
  "output": {
   "type": "object",
   "required": [
    "type"
   ],
   "properties": {
    "type": {
     "type": "string"
    },
    "example": {
     "type": "object",
     "required": [
      "version",
      "offerId",
      "amountBaseUnits",
      "inputDigest",
      "result",
      "boundaries",
      "receiptDigest"
     ],
     "properties": {
      "result": {
       "type": "object"
      },
      "offerId": {
       "enum": [
        "quantum-measurement-uncertainty"
       ],
       "type": "string"
      },
      "version": {
       "enum": [
        "maha-microproducts/0.1"
       ],
       "type": "string"
      },
      "boundaries": {
       "type": "array",
       "maxItems": 128,
       "minItems": 0
      },
      "inputDigest": {
       "type": "string",
       "maxLength": 71
      },
      "receiptDigest": {
       "type": "string",
       "maxLength": 71
      },
      "amountBaseUnits": {
       "enum": [
        "12001"
       ],
       "type": "string"
      }
     },
     "additionalProperties": false
    }
   }
  }
 }
}
```

## More

- Live health (JSON, refreshed every minute): https://www.zero.xyz/c/maha-strategies-quantum-measurement-uncertainty-binomial-shot-count-b50c8f2e/health.json
- [Zero catalog index](https://www.zero.xyz/llms.txt)
- [Other services from www.mahastrategies.com](https://www.zero.xyz/host/www.mahastrategies.com/llms.txt)