# Arrhenius OLS Fit for Rate-Temperature Data

> Arrhenius OLS Fit for Rate-Temperature Data is a paid API for AI agents from www.mahastrategies.com, paid per call via x402, $0.069001/call, status unknown (last checked 2026-10-26).

Fits positive rate-temperature observations to a log-linear Arrhenius model via OLS, returning activation energy, residuals, and transformed-fit errors.

## Facts

- Endpoint: POST https://www.mahastrategies.com/api/v1/micro/chemistry-arrhenius-fit?utm_source=zero.xyz
- Price: $0.069001/call
- Payment: x402
- Status: unknown
- Last checked: 2026-10-26
- Activations on Zero: 0
- Tags: x402
- Canonical page: https://www.zero.xyz/c/arrhenius-ols-fit-for-rate-temperature-data-d2d0aea0
- Structured record (JSON): https://api.zero.xyz/v1/capabilities/cap_a_so3CmKoaSk60yjuB_mk

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 arrhenius-ols-fit-for-rate-temperature-data-d2d0aea0 -d '<json body>'
```

Example prompt: Fit my rate-temperature data to the Arrhenius model using OLS — I have 5 temperatures in Kelvin [250, 273, 298, 323, 348] and corresponding rates [0.001, 0.003, 0.009, 0.025, 0.065], all public data, and I need the activation energy and residuals back.

## When to prefer this

Choose this endpoint when you need a transparent, auditable, no-extrapolation Arrhenius OLS regression on a small-to-moderate set of rate-temperature pairs (up to 128 points) and want explicit residuals and fit errors returned alongside the activation energy — particularly when you need receipt and digest provenance for the computation. Prefer it over generic statistics APIs when you specifically need the Arrhenius log-linear formulation without mechanistic claims.

## Known failure modes

- Array length mismatch between kelvin and rate arrays returns a validation error
- Arrays with fewer than 2 points cannot support regression and will be rejected
- Non-positive rate values cause log-transform failure (log-linear model requires positive rates)
- dataClass enum value outside 'public' or 'synthetic' returns schema validation error
- Arrays exceeding 128 items are rejected at schema level
- Payment failure or insufficient USDC balance prevents call execution

## How this service works

Fit positive rate-temperature observations by log-linear Arrhenius OLS; return activation energy, residuals and transformed-fit errors. No mechanism or extrapolation claim.

## Output

Returns a structured result containing the fitted activation energy (Ea) derived from the log-linear OLS slope, per-point residuals, transformed-fit errors, offer metadata (offerId, version, amountBaseUnits), an inputDigest for auditability, a receiptDigest, and any boundary annotations on the data points.

## 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",
      "kelvin",
      "rate"
     ],
     "properties": {
      "rate": {
       "type": "array",
       "maxItems": 128,
       "minItems": 1
      },
      "kelvin": {
       "type": "array",
       "maxItems": 128,
       "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": [
        "chemistry-arrhenius-fit"
       ],
       "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": [
        "69001"
       ],
       "type": "string"
      }
     },
     "additionalProperties": false
    }
   }
  }
 }
}
```

## More

- Live health (JSON, refreshed every minute): https://www.zero.xyz/c/arrhenius-ols-fit-for-rate-temperature-data-d2d0aea0/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)