feat: initial commit - oncology literature search platform

OncoLit: a multi-tenant oncology literature search, feed, and
collaboration platform. Built with FastAPI + Vue 3 + PostgreSQL.
Includes PubMed pipeline, drug approvals, AI summaries, and
systematic review tools.

check_hot_articles.py

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+import asyncio
+from sqlalchemy import text
+from sqlalchemy.ext.asyncio import create_async_engine
+
+DATABASE_URL = 'postgresql+asyncpg://scilit:scilit_prod_2026@postgres:5432/scilit'
+
+async def main():
+    engine = create_async_engine(DATABASE_URL)
+    async with engine.connect() as conn:
+        # Check cited_by_count distribution
+        r = await conn.execute(text("""
+            SELECT 
+                CASE 
+                    WHEN cited_by_count IS NULL OR cited_by_count = 0 THEN '0 or NULL'
+                    WHEN cited_by_count BETWEEN 1 AND 5 THEN '1-5'
+                    WHEN cited_by_count BETWEEN 6 AND 20 THEN '6-20'
+                    WHEN cited_by_count BETWEEN 21 AND 100 THEN '21-100'
+                    ELSE '100+'
+                END as bucket,
+                COUNT(*) as cnt,
+                MAX(cited_by_count) as max_in_bucket
+            FROM global_literature
+            GROUP BY bucket
+            ORDER BY MIN(COALESCE(cited_by_count, 0))
+        """))
+        print('=== Cited by count distribution ===')
+        for row in r:
+            print(f'  {row.bucket}: {row.cnt}')
+        
+        # Latest citation update time
+        r = await conn.execute(text("""
+            SELECT MAX(updated_at) as last_update, COUNT(*) as total_with_citations
+            FROM global_literature WHERE cited_by_count IS NOT NULL AND cited_by_count > 0
+        """))
+        for row in r:
+            print(f'\nLast citation update: {row.last_update}')
+            print(f'Articles with citations: {row.total_with_citations}')
+        
+        # Check what refresh_hot_articles_cache filters by
+        r = await conn.execute(text("""
+            SELECT cited_by_count, pub_date, pmid FROM global_literature
+            WHERE cited_by_count IS NOT NULL AND cited_by_count > 0
+            AND pub_date >= CURRENT_DATE - INTERVAL '365 days'
+            ORDER BY cited_by_count DESC LIMIT 10
+        """))
+        print('\nTop cited articles in last year:')
+        for row in r:
+            print(f'  PMID={row.pmid} cited={row.cited_by_count} pub_date={row.pub_date}')
+        
+    await engine.dispose()
+
+asyncio.run(main())