fix: restore stage-based Alpha check classification

backend/app/alphas.py

@@ -7,7 +7,7 @@ from datetime import datetime
 from sqlalchemy import or_, select, update
 
 from .models import Alpha, Research, ResearchTag, SelfCorrelation, now
-from .platform_checks import split_checks, submission_limits
+from .platform_checks import check_result, split_checks, submission_limits
 from .research.provenance import source_alpha_ids
 
 METRIC_FIELDS = (
@@ -20,16 +20,17 @@ def failed_checks(checks):
     """Return failed Alpha check names, excluding submission limits and local correlation."""
     return [
         check.get("name") if isinstance(check.get("name"), str) else "未命名检查"
-        for check in split_checks(checks)[0] if isinstance(check, dict) and check.get("result") == "FAIL"
+        for check in split_checks(checks)[0] if isinstance(check, dict) and check_result(check) == "FAIL"
     ] if isinstance(checks, list) else []
 
 
-def snapshot_columns(settings, metrics, checks):
+def snapshot_columns(settings, metrics, checks, *, checked=False):
     """Derive list fields from a platform snapshot, preserving missing metrics as null.
 
     Submission limits are excluded. Only explicit Alpha FAIL results count.
-    Empty, malformed and unfinished Alpha checks are
-    pending; all known checks passing without PROD_CORRELATION is only a pre-check.
+    Sync snapshots with no failures are PRE_CHECK; a completed explicit /check
+    with no failures is PASS. WARNING/PENDING do not count as failures, matching
+    the legacy workflow. Empty, malformed or unknown results remain PENDING.
     No submission eligibility or activity eligibility is inferred here.
     """
     settings = settings if isinstance(settings, dict) else {}
@@ -40,10 +41,10 @@ def snapshot_columns(settings, metrics, checks):
     by_name = {check["name"]: check for check in valid if isinstance(check.get("name"), str)}
     if failures:
         check_type = "FAIL_1" if failures == 1 else "FAIL_2"
-    elif not checks or len(valid) != len(checks) or any(check.get("result") != "PASS" for check in valid):
+    elif not checks or len(valid) != len(checks) or any(check_result(check) not in ("PASS", "WARNING", "PENDING") for check in valid):
         check_type = "PENDING"
     else:
-        check_type = "PASS" if "PROD_CORRELATION" in by_name else "PRE_CHECK"
+        check_type = "PASS" if checked else "PRE_CHECK"
     # /check values are freshest; submitted snapshots also expose a scalar in IS.
     prod_correlation = number(by_name.get("PROD_CORRELATION", {}).get("value"))
     if prod_correlation is None:
@@ -66,12 +67,13 @@ def snapshot_columns(settings, metrics, checks):
     }
 
 
-def check_summary(checks):
+def check_summary(checks, *, check_type):
     """Separate cached Alpha findings from submission limits; infer no live eligibility."""
     return {
-        "check_type": snapshot_columns({}, {}, checks)["check_type"],
+        "check_type": check_type,
         "failed_checks": failed_checks(checks),
         "submission_limits": submission_limits(checks),
+        "meaning": "PRE_CHECK 为同步无失败项；PASS 为主动检查完成且无失败项。PENDING/WARNING 不算失败，不代表全部检查项 PASS 或当前可提交",
     }