Raw Market Observations
Collect publicly observable product and pricing records from eligible market sources.
How GrapeCat Chem collects, normalizes, validates, and calculates cross-border chemical market price indexes.
Each published comparison passes through a controlled identity, specification, normalization, and validation pipeline.
Collect publicly observable product and pricing records from eligible market sources.
Map listings to CAS Number, chemical name, molecular formula, and recognized synonyms.
Separate observations by purity, grade, concentration, and product specification.
Normalize compatible package quantities such as mL, L, g, and kg into comparable units.
Convert regional pricing into a common comparison currency using a documented FX reference.
Remove clearly anomalous, incomplete, duplicate, or statistically inconsistent observations.
Calculate representative US and China regional price indexes using qualified observations.
Calculate the percentage difference between comparable regional indexes.
Raw Data → Identity Matching → Specification Matching → Unit Normalization → FX Normalization → Outlier Filtering → Regional Index → Variance
The index is a representative statistical value. It is not copied from one supplier listing and is not an executable quotation.
Positive variance indicates that the China regional index is lower than the US regional index. Negative variance indicates that the China regional index is higher.
Normalization improves comparability only where chemical identity and commercial specification permit a defensible comparison.
| Dimension | Method |
|---|---|
| CAS Identity | Observations are grouped primarily by CAS Number |
| Purity | Different purity levels are not automatically treated as equivalent |
| Grade | AR, HPLC, LC-MS, ACS and other grades are separated where applicable |
| Package Size | Prices are normalized only where package conversion is considered comparable |
| Weight / Volume | Mass and volume units are not blindly converted without appropriate chemical context |
| Currency | Regional prices are converted using the applicable FX reference |
| Duplicates | Duplicate or materially identical observations may be removed |
| Outliers | Abnormal observations may be excluded from index calculation |
Chemical, Compare, and Bulk return a methodVersion with each regional index. This registry reads the corresponding reviewed explanation through the same backend boundary.
Synthetic development method used to exercise the database, Go API, and frontend regional-index contract. Values are not production market intelligence.
Registry updated 2026-09-07
Synthetic full-detail method used for the 2-Fluorobenzoic Acid multi-basis showcase. Values validate complete History, confidence, supplier coverage, and comparison-basis rendering only.
Registry updated 2026-09-07
Regional-index API responses carry versioned confidence, observation counts, supplier coverage, and calculation timestamps when those values are available.
Confidence indicators describe the quality and comparability of the underlying dataset, not the quality of any supplier or chemical product.
Versioned server-side resultChemical price indexes are time-sensitive. Each index carries its own observation, verification, effective, and calculation times; the registry above explains the policy for its exact methodVersion.
Observation count and freshness values shown on Chemical, Compare, and Bulk come from the regional-index API. This page does not publish fixed example counts or dates that could disagree with those records.
Representative normalized market price derived from qualified regional observations.
A data point that contains sufficient identity, specification, package, and pricing information for comparison.
A transformed price used to improve comparability across compatible package sizes, currencies, or units.
The percentage difference between comparable US and China regional indexes.
The amount of time since underlying market observations were last refreshed.
An indicator describing the statistical coverage and comparability of the underlying dataset.
Apply the methodology framework to the current market index directory.