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Arrhenius OLS Fit for Rate-Temperature Data
x402
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.
Price / call$0.069001
Success—
StatusUnknown
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.
Example use cases
Activation energy from lab kinetics
“I measured reaction rates at six temperatures in Kelvin — 280, 290, 300, 310, 320, and 330 — with rates 0.0012, 0.0031, 0.0078, 0.019, 0.045, 0.10. All public data. Can you fit these to the Arrhenius equation and give me the activation energy and residuals?”
Validating synthetic kinetic dataset
“I generated a synthetic dataset of 10 rate-temperature pairs for testing — temperatures in Kelvin from 200 to 380 and estimated rates. Run an Arrhenius OLS fit on them (data class is synthetic) and show me the activation energy and any fit errors.”
Cross-checking published activation energy
“I have 8 rate observations from a published paper at temperatures 293, 303, 313, 323, 333, 343, 353, and 363 K with rates 0.002, 0.005, 0.011, 0.024, 0.051, 0.104, 0.21, 0.40 — these are public data. Fit them to the Arrhenius model and tell me the activation energy and residuals so I can compare with the paper's reported Ea.”
Technical details
Endpoint
POSThttps://www.mahastrategies.com/api/v1/micro/chemistry-arrhenius-fit?utm_source=zero.xyzWhen to prefer
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.
Side effects
- 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
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| inputrequired | object | |
| output | object |
Tags
x402
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