fix(fetch-caliber): 取数层排除半年/预测伪期间 + subjects 响应补 entity_id

R3 期间口径（仅 YYYY-MM）延伸到取数层：新增 alert_entity_scope.month_period_clause()（跨库可移植 SQL 等价式），应用到 15 个文件 26 处「按 period 倒序取最新值/最近N期」位点；dashboard 原 MySQL-only REGEXP 正则收口到同单一事实源。

GET /api/cma/subjects 响应增补 entity_id（NULL=全局标准准则科目 / N=账套私有明细），既有 10 字段语义与名称不变。

证据：pending-tasks/_reports/yanxue-20260924-cma-fetch-caliber-fixes-fullstack.md（改前/改后 A/B：F_NET_PROFIT 2026-H2/-55.0 → 2026-08/-10.46）。新增 7 例回归测试；全量 1 failed(预存在) 1473 passed，基线同项。

backend/app/api/kpi_causality.py

@@ -13,6 +13,7 @@ from app.deps import get_entity_id
 from app.auth_middleware import require_auth, require_role
 from app.models import KPIDefinition, KPICausality, KPIValue, OperationLog
 from app.utils.oplog import log_op
+from app.utils.alert_entity_scope import month_period_clause
 from app.services.causality_verification import (
     ALL_STATUSES,
     ALL_SOURCE_TYPES,
@@ -147,7 +148,7 @@ def simulate_causality(data: dict, db: Session = Depends(get_db), entity_id: int
     )
     if period:
         query_values = query_values.filter(KPIValue.period == period)
-    latest = query_values.order_by(KPIValue.period.desc()).first()
+    latest = query_values.filter(month_period_clause(KPIValue.period)).order_by(KPIValue.period.desc()).first()
     if latest:
         current_value = latest.actual_value
 
@@ -188,6 +189,7 @@ def simulate_causality(data: dict, db: Session = Depends(get_db), entity_id: int
             tgt_val = db.query(KPIValue).filter(
                 KPIValue.kpi_id == target_id,
                 KPIValue.actual_value.isnot(None),
+                month_period_clause(KPIValue.period),
             ).order_by(KPIValue.period.desc()).first()
 
             predicted_value = None