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cff-version: 1.2.0
message: "If you cite DotCheck engines or measured holdout gates, use the citation below."
title: "DotCheck AI-likeness engines (inhouse@5, inhouse-text@9, inhouse-video@2)"
authors:
  - name: "DotCheck"
url: "https://dotcheck.ai"
repository-code: "https://huggingface.co/DotCheck"
license: "Apache-2.0"
date-released: "2026-07-26"
abstract: >-
  DotCheck serves binary AI-likeness scores for images (wire inhouse@5 /
  Vermeer), text (inhouse-text@9 / Valla, seven languages), and video frame
  bags (inhouse-video@2 / Muybridge) using linear/logistic heads on frozen
  commercial-clean backbones. Live heads are published under Apache-2.0 on
  Hugging Face; everyday product scoring runs through DotCheck.
keywords:
  - ai-detection
  - image-classification
  - text-classification
  - video
  - siglip2
preferred-citation:
  type: soft
  authors:
    - name: "DotCheck"
  title: "DotCheck engines (inhouse@5, inhouse-text@9, inhouse-video@2)"
  url: "https://dotcheck.ai/docs"
  year: 2026