fix(ssa): Fix 7 integration bugs and refactor frontend unified state management

Bug fixes:
- Fix garbled error messages in chat (TypeWriter rendering issue)
- Fix R engine NA crash in descriptive.R (defensive isTRUE/is.na checks)
- Fix intent misclassification for statistical significance queries
- Fix step 2 results not displayed (accept warning status alongside success)
- Fix incomplete R code download (only step 1 included)
- Fix multi-task state confusion (clicking old card shows new results)
- Add R engine and backend parameter logging for debugging

Refactor - Unified Record Architecture:
- Replace 12 global singleton fields with AnalysisRecord as single source of truth
- Remove isWorkflowMode branching across all components
- One Analysis = One Record = N Steps paradigm
- selectRecord only sets currentRecordId, all rendering derives from currentRecord
- Fix cross-hook-instance issue: executeWorkflow fallback to store currentRecordId

Updated files: ssaStore, useWorkflow, useAnalysis, SSAChatPane, SSAWorkspacePane,
SSACodeModal, WorkflowTimeline, QueryService, WorkflowExecutorService, descriptive.R

Tested: Manual integration test passed - multi-task switching, R code completeness
Co-authored-by: Cursor <cursoragent@cursor.com>

backend/scripts/seed-ssa-intent-prompt.ts

@@ -79,7 +79,15 @@ const SSA_INTENT_PROMPT = `你是一个临床统计分析意图理解引擎。
 {"goal":"regression","outcome_var":"Death","outcome_type":"binary","predictor_vars":["Age","BMI","Smoking","Stage"],"predictor_types":["continuous","continuous","binary","categorical"],"grouping_var":null,"design":"independent","confidence":0.8,"reasoning":"用户想分析影响死亡率的因素，Death是二分类结局，其余变量作为预测因素纳入logistic回归"}
 \`\`\`
 
-### 示例 4：模糊表达 — 需要追问
+### 示例 4：统计学意义/检验
+用户: "Yqol和bmi是否有统计学意义？"
+数据画像中有: Yqol [numeric], bmi [numeric], sex [categorical], age [numeric]
+输出:
+\`\`\`json
+{"goal":"correlation","outcome_var":"Yqol","outcome_type":"continuous","predictor_vars":["bmi"],"predictor_types":["continuous"],"grouping_var":null,"design":"independent","confidence":0.85,"reasoning":"用户想了解Yqol和bmi之间是否存在统计学显著关系，两者都是连续变量，适合相关分析或回归分析"}
+\`\`\`
+
+### 示例 5：模糊表达 — 需要追问
 用户: "帮我分析一下这份数据"
 数据画像中有: 10个变量
 输出:
@@ -87,7 +95,7 @@ const SSA_INTENT_PROMPT = `你是一个临床统计分析意图理解引擎。
 {"goal":"descriptive","outcome_var":null,"outcome_type":null,"predictor_vars":[],"predictor_types":[],"grouping_var":null,"design":"independent","confidence":0.35,"reasoning":"用户没有指定任何分析目标和变量，只能先做描述性统计，建议追问具体分析目的"}
 \`\`\`
 
-### 示例 5：队列研究
+### 示例 6：队列研究
 用户: "我想做一个完整的队列研究分析，看看新药对预后的影响"
 数据画像中有: Drug [categorical, 2个水平], Outcome [categorical, 2个水平: 0/1], Age [numeric], Gender [categorical], BMI [numeric], Comorbidity [categorical]
 输出:
@@ -127,7 +135,7 @@ async function main() {
         content: SSA_INTENT_PROMPT,
         model_config: { model: 'deepseek-v3', temperature: 0.3, maxTokens: 2048 },
         status: 'ACTIVE',
-        changelog: `Phase Q v1.0: 5 组 Few-Shot + Confidence Rubric 客观化`,
+        changelog: `Phase Q v1.1: 6 组 Few-Shot (增加统计学意义示例) + Confidence Rubric 客观化`,
         created_by: 'system-seed',
       }
     });