Add multi-factor conviction gate to activation

Make "qualified" mean an edge candidate, not just R:R + confidence.
The gate now also requires (all admin-configurable, defaults on):
- high conviction: recommended_action LONG_HIGH / SHORT_HIGH only
- clean read: risk_level Low (no contradicting signals)
- probable primary target: best target probability >= min (default 60)

- Shared predicate: app/services/qualification.py +
  frontend/src/lib/qualification.ts (mirrored)
- Activation config extended (min_target_probability,
  require_high_conviction, exclude_conflicts) with bool-aware
  get/update + validation
- /trades/performance switched to ?qualified_only=true, applying
  the full gate server-side; confidence breakdown stays unfiltered
- Dashboard "Qualified", Signals "Qualified only" toggle, and
  Track Record all use the one gate; Admin gains the new controls

Sentiment provider runtime config (prior change) included.

Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>

app/scheduler.py

@@ -29,13 +29,14 @@ from app.models.ohlcv import OHLCVRecord
 from app.models.settings import SystemSetting
 from app.models.sentiment import SentimentScore
 from app.models.ticker import Ticker
+from app.exceptions import ProviderError
 from app.providers.alpaca import AlpacaOHLCVProvider
 from app.providers.fundamentals_chain import build_fundamental_provider_chain
-from app.providers.openai_sentiment import OpenAISentimentProvider
 from app.providers.protocol import SentimentData
 from app.services import fundamental_service, ingestion_service, sentiment_service
 from app.services.outcome_service import evaluate_pending_setups
 from app.services.rr_scanner_service import scan_all_tickers
+from app.services.sentiment_provider_service import build_sentiment_provider
 from app.services.ticker_universe_service import bootstrap_universe
 
 logger = logging.getLogger(__name__)
@@ -407,13 +408,13 @@ async def collect_sentiment() -> None:
         total = len(symbols)
         _runtime_progress(job_name, processed=0, total=total)
 
-        if not settings.openai_api_key:
-            logger.warning(json.dumps({"event": "job_skipped", "job": job_name, "reason": "openai key not configured"}))
-            _runtime_finish(job_name, "skipped", processed=0, total=total, message="OpenAI key not configured")
-            return
-
         try:
-            provider = OpenAISentimentProvider(settings.openai_api_key, settings.openai_model)
+            async with async_session_factory() as cfg_db:
+                provider = await build_sentiment_provider(cfg_db)
+        except ProviderError as exc:
+            logger.warning(json.dumps({"event": "job_skipped", "job": job_name, "reason": str(exc)}))
+            _runtime_finish(job_name, "skipped", processed=0, total=total, message=str(exc))
+            return
         except Exception as exc:
             logger.error(json.dumps({"event": "job_error", "job": job_name, "error_type": type(exc).__name__, "message": str(exc)}))
             _runtime_finish(job_name, "error", processed=0, total=total, message=str(exc))