fix: 排序作用于组内事件+时间线限高滚动+UTM别名归一消冲突误报

- attribution.py：新增 _canon 归一（小写/去协议与域名后缀/别名表 fb→facebook、百度→baidu 等/仅留字母数字汉字），
  冲突判定改为两路各自归一后比较——同源升级 combined 并在 detail 记 utm_source 原文，仍不同才 conflict
- detail.vue：orderedDays 组内会话/事件同步翻转（desc=组与组内都最新在前，asc=都最早在前）；
  .tl-body 限高 calc(100vh - 380px) 卡内滚动，日期组头随内容滚动
- test_attribution.py：+4 用例（fb↔facebook、chatgpt.com↔ChatGPT、google↔facebook 仍冲突、百度↔baidu）

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

server/tracker/services/attribution.py

@@ -19,6 +19,10 @@ from tracker import constants as C
 _CTRL_CHARS = re.compile(r"[\x00-\x1f\x7f]")
 _GENERIC_TLDS = ("com",)   # 引擎 host 落在这些 TLD 时不作为国家 variant 显示
 
+# UTM 标签 ↔ 平台名别名（冲突判定前归一）：缩写/中文品牌名 → 标准名；baidu 恒等仅为可读
+_UTM_ALIASES = {"fb": "facebook", "ig": "instagram", "tt": "tiktok",
+                "wa": "whatsapp", "g": "google", "baidu": "baidu", "百度": "baidu"}
+
 
 def _host(url: str) -> str:
     """提取 referrer host；异常/空 → ""。hostname 自动去端口并小写。"""
@@ -88,6 +92,22 @@ def _in_app_name(ua: str) -> str:
     return ""
 
 
+def _canon(name: str) -> str:
+    """平台名/UTM 标签宽松归一（仅用于冲突判定）：小写 → 去协议与路径 → 去 www. 前缀
+    → 去最后一段域名后缀（chatgpt.com→chatgpt、google.ru→google）→ 别名表 → 仅留
+    字母数字（含汉字）。fb↔Facebook、百度↔baidu 归一后同源，不再误报 conflict。"""
+    s = (name or "").lower().strip()
+    if "://" in s:
+        s = s.split("://", 1)[1]
+    s = s.split("/", 1)[0]
+    if s.startswith("www."):
+        s = s[4:]
+    if "." in s:
+        s = s.rsplit(".", 1)[0]
+    s = _UTM_ALIASES.get(s, s)
+    return re.sub(r"[^0-9a-z一-鿿]", "", s)
+
+
 def _utm_channel(label: str) -> str:
     """UTM 标签尽力归类：已知 AI/引擎/社交标签（裸标签 "baidu"/显示名 "Google" 皆可）
     映射到对应渠道，未知 → referral（有名来源，可信度由 label_only 单独表达）。"""
@@ -150,8 +170,10 @@ def classify(*, referrer_url: str = "", utm: dict | None = None,
     # UTM 证据叠加：观察结论之上只做印证/并列，不覆盖
     if utm_source:
         if out["resolution"] == "resolved":
-            if utm_source.lower() == out["platform"].lower():
+            if _canon(utm_source) == _canon(out["platform"]):
+                # 归一后同源 → 互相印证；UTM 原文并记进 detail（顶层展示观察结论）
                 out["evidence_kind"] = "combined"
+                out["detail"] = {**out["detail"], "utm_source": utm_source}
             else:   # 矛盾：观察证据保留在顶层，两路证据各自完整并列进 detail
                 out["resolution"] = "conflict"
                 out["detail"] = {**out["detail"],

server/tracker/tests/test_attribution.py

@@ -113,6 +113,38 @@ def test_utm_contradicting_referrer_is_conflict_with_both_evidences():
     assert utm_ev["platform"] == "google" and utm_ev["evidence_kind"] == "utm_label"
 
 
+# ------------------------------------------- 别名归一（消 conflict 误报）
+def test_utm_alias_fb_matches_facebook_referrer():
+    r = classify(referrer_url="https://facebook.com/l/abc", utm={"utm_source": "fb"})
+    assert r["resolution"] != "conflict"                # fb↔Facebook 归一后同源，不是矛盾
+    assert r["channel"] == "social" and r["platform"] == "Facebook"
+    assert r["evidence_kind"] == "combined"
+    assert r["detail"].get("utm_source") == "fb"        # 归一对齐时原文并记进 detail
+
+
+def test_utm_with_domain_suffix_matches_bare_platform():
+    r = classify(referrer_url="https://chatgpt.com/c/abc", utm={"utm_source": "chatgpt.com"})
+    assert r["evidence_kind"] == "combined"             # chatgpt.com → chatgpt 与 ChatGPT 同源
+    assert r["platform"] == "ChatGPT"
+    assert r["detail"].get("utm_source") == "chatgpt.com"
+    r2 = classify(referrer_url="https://www.google.com/search?q=x",
+                  utm={"utm_source": "google.ru"})      # 国家域名后缀 → google
+    assert r2["evidence_kind"] == "combined" and r2["platform"] == "Google"
+
+
+def test_utm_alias_still_conflict_when_platforms_differ():
+    r = classify(referrer_url="https://facebook.com/l/abc", utm={"utm_source": "google"})
+    assert r["resolution"] == "conflict"                # 归一后仍不同 → 保持矛盾并列
+
+
+def test_utm_chinese_alias_baidu_matches():
+    r = classify(referrer_url="https://www.baidu.com/s?wd=x", utm={"utm_source": "百度"})
+    assert r["resolution"] != "conflict"                # 百度 ↔ baidu.com(平台"百度") 同源
+    assert r["channel"] == "natural_search" and r["platform"] == "百度"
+    assert r["evidence_kind"] == "combined"
+    assert r["detail"].get("utm_source") == "百度"
+
+
 def test_utm_only_is_label_only():
     r = classify(utm={"utm_source": "newsletter"})
     assert r["channel"] == "referral"               # 未知标签 → 有名 referral，但状态诚实标注