refactor: reorganize analysis data to support multiple runs

Strategy: key runs by bicorder version (not date), promote shared inputs
to analysis/data/, and stamp every output with its bicorder_version so
a re-run on edited gradients is self-describing.

Data layout:
- Promote the shared protocol inputs out of the run directory:
    analysis/data/protocols_edited.csv  (411 cleaned protocols)
    analysis/data/protocols_raw.csv     (774 un-cleaned entries)
- Rename the v1.2.6 synthetic run:
    data/synthetic_20251116/ -> data/synthetic_1.2.6/
  so the bicorder version it was scored against is explicit (gradient
  structure changes between versions make date-based names ambiguous)

Provenance:
- bicorder_analyze.py now writes a 'bicorder_version' column into every
  output readings.csv, recording which gradient structure produced it

Scripts:
- Update the real code defaults that pointed at the old run path
  (bicorder_classifier.py, classify_readings.py, sync_readings.sh,
  compare_analyses.py) and refresh docstring/help examples
- Remove a stray committed __pycache__/.pyc

Docs: analysis/README.md documents the new layout + how to add a run;
WORKFLOW.md, TEST_COMMANDS.md, INTEGRATION_GUIDE.md paths updated.

analysis/scripts/bicorder_analyze.py

@@ -55,6 +55,7 @@ def process_csv(input_csv, output_csv, bicorder_path, analyst=None, standpoint=N
     # Load bicorder configuration
     bicorder_data = load_bicorder_config(bicorder_path)
     gradients = extract_gradients(bicorder_data)
+    bicorder_version = bicorder_data.get('version', '')
 
     with open(input_csv, 'r', encoding='utf-8') as infile, \
          open(output_csv, 'w', newline='', encoding='utf-8') as outfile:
@@ -68,6 +69,9 @@ def process_csv(input_csv, output_csv, bicorder_path, analyst=None, standpoint=N
         gradient_columns = [g['column_name'] for g in gradients]
         output_fields = list(original_fields) + gradient_columns
 
+        # Add the bicorder version as a provenance column
+        output_fields.append('bicorder_version')
+
         # Add metadata columns if provided
         if analyst is not None:
             output_fields.append('analyst')
@@ -87,6 +91,9 @@ def process_csv(input_csv, output_csv, bicorder_path, analyst=None, standpoint=N
             for gradient in gradients:
                 output_row[gradient['column_name']] = ''
 
+            # Record which bicorder version these gradients came from
+            output_row['bicorder_version'] = bicorder_version
+
             # Add metadata if provided
             if analyst is not None:
                 output_row['analyst'] = analyst