remove min_target_probability gate + add chart time-range presets

min_target_probability is gone: it filtered on the probability model the
calibration has repeatedly shown to be weak and overconfident, it was redundant
with the momentum gate, and as an off-by-default knob it just invited bad tuning.
Removed from the backend gate, activation config/schema, the frontend mirror
(qualifiesSetup / activationSummary), and ActivationSettings. The probability
model stays where it does real work (primary-target selection + display).

Charts: with multi-year history the all-bars default was unreadable. Added
time-range presets (1M / 3M / 6M / YTD / 1Y / 3Y / 5Y / All), defaulting to 1Y;
clicking a preset always re-applies (snaps back after a manual zoom). Y-axis
autoscale and wheel-zoom / drag-pan were already there.

339 backend tests pass; frontend build clean.

Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>

tests/unit/test_activation_settings.py

@@ -28,7 +28,6 @@ class TestActivationConfig:
             "min_momentum_percentile": 80.0,
             "min_rr": 1.2,
             "min_confidence": 55.0,
-            "min_target_probability": 0.0,
             "require_high_conviction": False,
             "exclude_conflicts": False,
         }
@@ -57,12 +56,11 @@ class TestActivationConfig:
     async def test_conviction_flags_round_trip(self, session: AsyncSession):
         await update_activation_config(
             session,
-            {"require_high_conviction": False, "exclude_conflicts": False, "min_target_probability": 45.0},
+            {"require_high_conviction": True, "exclude_conflicts": True},
         )
         config = await get_activation_config(session)
-        assert config["require_high_conviction"] is False
-        assert config["exclude_conflicts"] is False
-        assert config["min_target_probability"] == 45.0
+        assert config["require_high_conviction"] is True
+        assert config["exclude_conflicts"] is True
 
     async def test_rejects_negative_rr(self, session: AsyncSession):
         with pytest.raises(ValidationError):
@@ -71,7 +69,3 @@ class TestActivationConfig:
     async def test_rejects_out_of_range_confidence(self, session: AsyncSession):
         with pytest.raises(ValidationError):
             await update_activation_config(session, {"min_confidence": 120.0})
-
-    async def test_rejects_out_of_range_target_probability(self, session: AsyncSession):
-        with pytest.raises(ValidationError):
-            await update_activation_config(session, {"min_target_probability": 150.0})

tests/unit/test_qualification.py

@@ -12,7 +12,6 @@ DEFAULT_GATE = {
     "min_momentum_percentile": 0.0,
     "min_rr": 1.2,
     "min_confidence": 55.0,
-    "min_target_probability": 0.0,
     "require_high_conviction": False,
     "exclude_conflicts": False,
 }
@@ -25,7 +24,6 @@ STRICT_GATE = {
     "min_momentum_percentile": 0.0,
     "min_rr": 2.0,
     "min_confidence": 70.0,
-    "min_target_probability": 60.0,
     "require_high_conviction": True,
     "exclude_conflicts": True,
 }
@@ -112,9 +110,6 @@ class TestStrictTighteners:
         s = _setup(risk_level="Medium", targets=[{"probability": 65.0, "is_primary": True}])
         assert setup_qualifies(s, STRICT_GATE) is False
 
-    def test_low_target_probability_fails(self):
-        assert setup_qualifies(_setup(targets=[{"probability": 40.0, "is_primary": True}]), STRICT_GATE) is False
-
 
 class TestBestTargetProbability:
     def test_returns_max(self):