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explanation.py

@@ -104,21 +104,50 @@ def generate_forensic_report(verdict: ForensicVerdict) -> str:
 
 """
     
-    # Fix 5: Add modality disclosure when suppression was active
+    # Modality section — ALWAYS shown for diagnostic transparency
     modality_info = verdict.reasoning_tree.get("modality", {})
     detected_modality = modality_info.get("detected", "UNKNOWN")
     n_adjustments = modality_info.get("adjustments_applied", 0)
+    indicators = modality_info.get("indicators", {})
+    
+    modality_labels = {
+        "PORTRAIT_MODE": "smartphone portrait/bokeh mode",
+        "MESSAGING": "messaging app (WhatsApp, Telegram, etc.)",
+        "SOCIAL_MEDIA": "social media platform",
+        "SCREENSHOT": "screen capture",
+        "SMARTPHONE": "standard smartphone camera",
+        "DSLR": "DSLR/mirrorless camera",
+        "MACRO_DSLR": "DSLR macro/shallow DoF photography",
+        "UNKNOWN": "unknown (no suppression applied)",
+    }
+    label = modality_labels.get(detected_modality, detected_modality)
+    
+    report += f"""---
+
+## 📱 Capture Modality Detection
+
+**Detected:** {detected_modality} — {label}  
+**Confidence:** {modality_info.get('confidence', 0):.0%}  
+**Tests recalibrated:** {n_adjustments}
+
+**Detection signals:**
+- Bayer CFA pattern: {'✅ Present' if indicators.get('has_bayer') else '❌ Absent'} (margin={indicators.get('bayer_margin', 0)})
+- Peak sharpness (p95): {indicators.get('p95_sharpness', '?')}
+- Bimodal ratio: {indicators.get('bimodal_ratio', '?')}
+- Sharpness ratio (center/edge): {indicators.get('sharpness_ratio', '?')}
+- Blur uniformity: {indicators.get('blur_uniformity', '?')}
+- Has genuine detail: {indicators.get('has_detail', '?')}
+"""
+    if indicators.get('safety_override'):
+        report += f"- ⚠️ **Safety override:** {indicators['safety_override']}\n"
+    if indicators.get('modality_scores'):
+        report += f"- Modality scores: {indicators['modality_scores']}\n"
+    if indicators.get('macro_detected'):
+        report += f"- 🔬 Macro photography detected (bg_color_std={indicators.get('bg_color_std', '?')})\n"
+    if indicators.get('portrait_detected'):
+        report += f"- 📱 Portrait mode detected\n"
     
     if detected_modality != "UNKNOWN" and n_adjustments > 0:
-        modality_labels = {
-            "PORTRAIT_MODE": "smartphone portrait/bokeh mode",
-            "MESSAGING": "messaging app (WhatsApp, Telegram, etc.)",
-            "SOCIAL_MEDIA": "social media platform",
-            "SCREENSHOT": "screen capture",
-            "SMARTPHONE": "standard smartphone camera",
-            "DSLR": "DSLR/mirrorless camera",
-        }
-        label = modality_labels.get(detected_modality, detected_modality)
         
         report += f"""---