Adjust Z-score classification and typos

Z-Score_Calculator.py

@@ -46,7 +46,7 @@ DISABLED_BIOMARKERS = {"weight", "sbp", "dbp", "pwv", "nb_vigorous_active_minute
 def main():
     if "disclaimer_shown" not in st.session_state:
         st.info(
-            "These calculations are dedicated for scientifically purposes only. "
+            "These calculations are dedicated for scientific purposes only. "
             "For detailed questions regarding personal health data contact your "
             "healthcare professionals."
         )

batch_utils.py

@@ -121,7 +121,7 @@ def process_batch_data(df: pd.DataFrame, normative_df: pd.DataFrame,
                     result[f'{biomarker}_z'] = round(res['z_score'], 2)
                     result[f'{biomarker}_percentile'] = round(res['percentile'], 1)
                     
-                    # Context-aware interpretation
+                    # Context-aware interpretation (Average = -0.5 to 0.5)
                     z = res['z_score']
                     higher_is_better = biomarker in HIGHER_IS_BETTER
                     
@@ -129,9 +129,9 @@ def process_batch_data(df: pd.DataFrame, normative_df: pd.DataFrame,
                         # For steps, sleep, activity: high is good
                         if z < -2:
                             result[f'{biomarker}_interpretation'] = 'Very Low ⚠️'
-                        elif z < -1:
+                        elif z < -0.5:
                             result[f'{biomarker}_interpretation'] = 'Below Average'
-                        elif z < 1:
+                        elif z < 0.5:
                             result[f'{biomarker}_interpretation'] = 'Average'
                         elif z < 2:
                             result[f'{biomarker}_interpretation'] = 'Above Average ✓'
@@ -141,9 +141,9 @@ def process_batch_data(df: pd.DataFrame, normative_df: pd.DataFrame,
                         # For HR, BP, PWV: low is good
                         if z < -2:
                             result[f'{biomarker}_interpretation'] = 'Very Low ✓✓'
-                        elif z < -1:
+                        elif z < -0.5:
                             result[f'{biomarker}_interpretation'] = 'Below Average ✓'
-                        elif z < 1:
+                        elif z < 0.5:
                             result[f'{biomarker}_interpretation'] = 'Average'
                         elif z < 2:
                             result[f'{biomarker}_interpretation'] = 'Above Average'
@@ -334,16 +334,16 @@ def generate_pdf_report(patient_info: dict, measurements: dict, z_scores: dict =
                 value = measurements.get(biomarker, 'N/A')
                 label = BIOMARKER_LABELS.get(biomarker, biomarker.replace('_', ' ').title())
                 
-                # Context-aware interpretation
+                # Context-aware interpretation (Average = -0.5 to 0.5)
                 higher_is_better = biomarker in HIGHER_IS_BETTER
                 
                 if higher_is_better:
                     # For steps, sleep, activity: high is good
                     if z < -2:
                         interp = "Very Low ⚠️"
-                    elif z < -1:
+                    elif z < -0.5:
                         interp = "Below Average"
-                    elif z < 1:
+                    elif z < 0.5:
                         interp = "Average"
                     elif z < 2:
                         interp = "Above Average ✓"
@@ -353,9 +353,9 @@ def generate_pdf_report(patient_info: dict, measurements: dict, z_scores: dict =
                     # For HR, BP, PWV: low is good
                     if z < -2:
                         interp = "Very Low ✓✓"
-                    elif z < -1:
+                    elif z < -0.5:
                         interp = "Below Average ✓"
-                    elif z < 1:
+                    elif z < 0.5:
                         interp = "Average"
                     elif z < 2:
                         interp = "Above Average"

pages/1_Batch_Analysis.py

@@ -266,3 +266,4 @@ st.markdown(
     "Built with ❤️ in Düsseldorf. © Lars Masanneck 2026."
 )
 
+

pages/2_PDF_Report.py

@@ -218,16 +218,16 @@ if st.button("📄 Generate PDF Report", type="primary"):
                             pct = data['percentile']
                             value = measurements[biomarker]
                             
-                            # Context-aware interpretation
+                            # Context-aware interpretation (Average = -0.5 to 0.5)
                             higher_is_better = biomarker in HIGHER_IS_BETTER
                             
                             if higher_is_better:
                                 # For steps, sleep, activity: high is good
                                 if z < -2:
                                     interp = "Very Low ⚠️"
-                                elif z < -1:
+                                elif z < -0.5:
                                     interp = "Below Average"
-                                elif z < 1:
+                                elif z < 0.5:
                                     interp = "Average"
                                 elif z < 2:
                                     interp = "Above Average ✓"
@@ -237,9 +237,9 @@ if st.button("📄 Generate PDF Report", type="primary"):
                                 # For HR: low is good
                                 if z < -2:
                                     interp = "Very Low ✓✓"
-                                elif z < -1:
+                                elif z < -0.5:
                                     interp = "Below Average ✓"
-                                elif z < 1:
+                                elif z < 0.5:
                                     interp = "Average"
                                 elif z < 2:
                                     interp = "Above Average"