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Where the numbers come from

Data transparency

Every price and every ranking position on this site is a function of counted credentials. This page lists the APIs and registries that feed those counts, the exact weight each credential carries, and the source passages the AI relied on when building an artist CV. Nothing here is an appraisal.

01 · Coverage of the current database

Artists

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With declared sources

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CVs with evidence

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Average confidence

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No AI refresh recorded yet. Records refresh automatically every day and can be refreshed on demand from the ranking.

02 · What feeds a record

The research pass consults these registries, then reconciles them into the counted credentials stored for each artist.

Metropolitan Museum of Art — Collection API

Open object endpoint used to confirm works held in the collection.

Public API

Feeds: Museum collections

Harvard Art Museums API

Person and exhibition records for institutional history.

Public API

Feeds: Museum collections · Exhibitions

Wikidata / Wikipedia

Identity data, birth and death years, practice and mediums.

Public registry

Feeds: Biography · Nationality · Dates · Mediums

Gallery and institution websites

Representation pages and exhibition archives published by the venues.

Public registry

Feeds: Gallery representation · Solo and group exhibitions

Auction house results

Published hammer results — reference only, never part of the cofactor.

Public registry

Feeds: Auction record

Lovable AI research pass

The model reconciles the sources above into counted credentials and a structured CV, and reports its own confidence.

Model research

Feeds: Counting, reconciliation and CV

Manual review screen

Values corrected by hand on the artist credential editor override the research pass.

Manual

Feeds: Any credential

03 · Sources actually cited

Registries the AI declared for the artists currently in the database, and which credentials each one supported.

Loading records…

04 · How a credential becomes a price

Each credential count is multiplied by its weight; the sum is the credential score. Cofactor = 1.5 + 2.4 × √score. Painting price = height (in) × width (in) × cofactor. Photography uses market precedent by size bracket and edition scarcity. The auction record is shown for reference and never enters the cofactor.

Museum exhibitions× 9 pts per unit
Museum collections× 6 pts per unit
Books× 4 pts per unit
Gallery representation× 4 pts per unit
Solo exhibitions× 3.5 pts per unit
Scholarly articles× 2.5 pts per unit
Group exhibitions× 1 pts per unit
Private collections× 0.6 pts per unit
Press× 0.5 pts per unit

05 · AI evidence in each CV

When a CV is generated, the AI also records the passages it relied on — the section, the entry they justify, the quoted material and the source. Open any artist from the ranking and read the “Transparency” block at the bottom of the panel. Entries generated before this feature was added show no passages until the CV is refreshed.

Estimated values in USD, derived from public data gathered by AI. Use as a reference, not as a formal appraisal.