Increase focus on confidence grades, scores are informational only

Signed-off-by: Fabiano Franz <contact@fabianofranz.com>

docs/concepts/confidence_scores.md

@@ -1,6 +1,6 @@
 ## Introduction
 
-**Confidence scores** were introduced in [v2.34.0](https://github.com/docling-project/docling/releases/tag/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`](../../reference/document_converter/#docling.document_converter.ConversionResult.confidence) field of the [`ConversionResult`](../../reference/document_converter/#docling.document_converter.ConversionResult) object returned by the document converter.
+**Confidence grades** were introduced in [v2.34.0](https://github.com/docling-project/docling/releases/tag/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`](../../reference/document_converter/#docling.document_converter.ConversionResult.confidence) field of the [`ConversionResult`](../../reference/document_converter/#docling.document_converter.ConversionResult) object returned by the document converter.
 
 ## Purpose
 
@@ -8,12 +8,16 @@ Complex layouts, poor scan quality, or challenging formatting can lead to subopt
 
 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.
 
-Use cases for confidence scores include:
+!!! 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:
 
 - Identify documents requiring manual review after the conversion
 - Adjust conversion pipelines to the most appropriate for each document type
 - Set confidence thresholds for unattended batch conversions
-- Catch potential conversion issues early in your workflow
+- Catch potential conversion issues early in your workflow.
 
 ## Concepts
 
@@ -21,41 +25,35 @@ Use cases for confidence scores include:
 
 A confidence report contains *scores* and *grades*:
 
-- **Scores**: Numerical values between 0.0 and 1.0, where higher values indicate better conversion quality
-- **Grades**: Categorical quality assessments based on score thresholds:
-  - `POOR`: Score < 0.5
-  - `FAIR`: Score < 0.8  
-  - `GOOD`: Score < 0.9
-  - `EXCELLENT`: Score ≥ 0.9
+- **Scores**: Numerical values between 0.0 and 1.0, where higher values indicate better conversion quality, for internal use only
+- **Grades**: Categorical quality assessments based on score thresholds, used to assess the overall conversion confidence:
+  - `POOR`
+  - `FAIR`
+  - `GOOD`
+  - `EXCELLENT`
 
-### Types of scores
+### Types of confidence calculated
 
-Each confidence report includes four component scores:
+Each confidence report includes four component scores and grades:
 
 - **`layout_score`**: Overall quality of text content extraction
 - **`ocr_score`**: Quality of OCR-extracted content
 - **`parse_score`**: 10th percentile score of text cells (emphasizes problem areas)
 - **`table_score`**: Table extraction quality *(not yet implemented)*
 
-### Summary scores
+### Summary grades
 
-Two aggregate scores provide overall document quality assessment:
+Two aggregate grades provide overall document quality assessment:
 
-- **`mean_score`**: Average of the four component scores
-- **`low_score`**: 5th percentile score (highlights worst-performing areas)
-
-Both summary scores include corresponding `mean_grade` and `low_grade` fields for quick quality assessment.
+- **`mean_grade`**: Average of the four component scores
+- **`low_grade`**: 5th percentile score (highlights worst-performing areas)
 
 ### Page-level vs document-level
 
-Confidence scores are calculated at two levels:
+Confidence grades are calculated at two levels:
 
-- **Page-level**: Individual scores for each page, stored in the `pages` field
-- **Document-level**: Overall scores for the entire document, calculated as averages of page-level scores and stored in fields equally named in the root [`ConfidenceReport`](h../../reference/document_converter/#docling.document_converter.ConversionResult.confidence)
-
-!!! note "Document-level scores"
-
-    For most use cases, users should safely focus on the document-level `mean_score` / `mean_grade` and `low_score` / `low_grade` fields to assess overall conversion quality.
+- **Page-level**: Individual scores and grades for each page, stored in the `pages` field
+- **Document-level**: Overall scores and grades for the entire document, calculated as averages of the page-level grades and stored in fields equally named in the root [`ConfidenceReport`](h../../reference/document_converter/#docling.document_converter.ConversionResult.confidence)
 
 ### Example