docs/concepts/confidence_scores.md
Confidence grades were introduced in v2.34.0 to help users understand how well a conversion performed and guide decisions about post-processing workflows. They are available in the confidence field of the ConversionResult object returned by the document converter.
Complex layouts, poor scan quality, or challenging formatting can lead to suboptimal document conversion results that may require additional attention or alternative conversion pipelines.
Confidence scores provide a quantitative assessment of document conversion quality. Each confidence report includes a numerical score (0.0 to 1.0) measuring conversion accuracy, and a quality grade (poor, fair, good, excellent) for quick interpretation.
!!! note "Focus on quality grades!"
Users can and should safely focus on the document-level grade fields — `mean_grade` and `low_grade` — to assess overall conversion quality. Numerical scores are used internally and are for informational purposes only; their computation and weighting may change in the future.
Use cases for confidence grades include:
A confidence report contains scores and grades:
POORFAIRGOODEXCELLENTEach confidence report includes four component scores and grades:
layout_score: Overall quality of document element recognitionocr_score: Quality of OCR-extracted contentparse_score: 10th percentile score of digital text cells (emphasizes problem areas)table_score: Table extraction quality (not yet implemented)Two aggregate grades provide overall document quality assessment:
mean_grade: Average of the four component scoreslow_grade: 5th percentile score (highlights worst-performing areas)Confidence grades are calculated at two levels:
pages fieldConfidenceReport